Shield, AI Jobs in Usa

Our client, a large, complex enterprise organization, is looking for a Principal AI Engineer to serve as the lead architect and hands-on builder of a unified AI Platform as a Service (PaaS) a secure, multi-tenant foundation that helps internal teams build and operate semantic discovery, conversational experiences, and autonomous agent workflows at scale.

Summary:

The Principal AI Engineer will design and build an enterprise-grade “AI operating layer” that turns modern foundation model capabilities into a governed, reusable platform used across multiple business domains. This role balances approximately 40% hands-on development with 60% platform strategy, personally building core orchestration services, standardized capability interfaces, and trust/safety guardrails. The platform will enable teams to deploy specialized agents that can collaborate via defined protocols, securely access grounded knowledge sources, and execute autonomous tasks within a controlled, high-availability runtime.

Location: Remote (U.S.) / Hybrid options may be available based on client needs.

Compensation Range: $145,000 - $250,000 per year plus RSUs & Bonus

Benefits: Very competitive benefits

Responsibilities

• Architect and deliver a self-service AI platform that provides reusable patterns, reference implementations, and standardized building blocks for internal engineering teams.
• Define and communicate a multi-year platform roadmap, ensuring technical priorities map to enterprise outcomes and adoption goals.
• Design and implement stateful orchestration (state graphs/state machines) to handle planning edge cases, recovery, and self-correction in autonomous workflows.
• Build and operate secure remote tool gateways (e.g., MCP-style servers) and implement controlled function-calling interfaces for connecting agents to sensitive enterprise systems.
• Establish interoperability standards for agent-to-agent collaboration, enabling autonomous discovery and reliable task handoffs across independently built agent solutions.
• Design an agent identity and authorization layer that supports fine-grained permissions, auditable actions, and strong accountability for autonomous behaviors.
• Implement a unified knowledge layer using semantic retrieval and multimodal grounding to support accurate, “source-aligned” responses and decisions.
• Build long-term context persistence (“memory”) using retrieval and graph-based storage to preserve institutional knowledge and improve continuity over time.
• Create a trust and evaluation layer with automated testing pipelines to measure quality, safety, cost, latency, and reliability of agent behavior across tenants.
• Own runtime lifecycle management for agent sessions, ensuring high availability, persistence, scalability, and controlled rollout patterns.
• Lead deep code reviews focused on agent-specific failure modes (runaway loops, tool misuse, state growth, unreliable calling patterns) and implement mitigations.
• Optimize inference performance and spend through techniques such as prompt caching, model routing, and workload-aware runtime strategies.
• Act as a technical multiplier by mentoring senior/staff engineers on advanced agentic patterns, evaluation methods, and production hardening.
• Partner closely with Cloud and Infrastructure teams to influence enabling services and platform primitives needed for enterprise AI delivery.
• Raise the bar on engineering quality via documentation, profiling, reliability improvements, and ongoing performance tuning.

QUALIFICATIONS:

Required:

• 10+ years of software engineering experience, including 4+ years operating at a Principal/Architect level.
• 2+ years architecting and shipping LLM-based systems, with demonstrated experience taking agentic solutions into production at scale.
• 5+ years working in agile delivery environments.
• Google Cloud Professional Cloud Architect certification.
• Proven ability to lead technical workstreams and translate business needs into durable platform architectures.
• Strong expertise in asynchronous orchestration (e.g., Python) plus proficiency in a statically typed language (Java, Go, or Rust) for high-concurrency platform services.
• Hands-on experience with stateful graph orchestration patterns and frameworks (e.g., LangGraph/ADK-style approaches) to power robust reasoning workflows.
• Strong cloud-native experience with CLI tooling and Infrastructure-as-Code; proven ability to deploy and scale containerized workloads using container orchestration and serverless platforms.
• Experience designing and operating distributed architectures at scale, including vector stores, graph databases, and structured data pipelines.
• Deep knowledge of multi-agent design patterns and the ability to extend or replace off-the-shelf orchestration when scaling, safety, or reliability requires it.
• Working understanding of modern agent reasoning approaches (Chain-of-Thought, ReAct, Tree-of-Thoughts, Self-Reflection) and when to apply them.
• Experience supporting very high request volumes and/or extremely large datasets in production environments.
• Expertise building semantic retrieval layers, attribute-aware discovery, and stateful persistence for long-lived agent context.
• Strong understanding of MCP-style tool protocols, agent-to-agent interaction patterns, REST/gRPC APIs, OAuth2, and function-calling mechanics.
• Familiarity with microservices architecture patterns and distributed systems best practices.
• Ability to implement observability for agentic systems, including traceability/telemetry and debugging methods for multi-step reasoning and handoffs.
• Awareness of global AI regulations (e.g., EU AI Act) and ability to translate requirements into technical controls and platform governance.
• Strong written and verbal communication skills across technical and business audiences.
• Calm, decisive execution in high-pressure or incident scenarios.
• Highly organized, self-directed, detail-oriented, and effective with limited supervision.
• Ability to support off-hours work as needed, including rotational on-call, weekends, and holidays.

Preferred:

• Bachelor’s or Master’s in Computer Science, AI, or a related field.
• PhD in AI, Distributed Systems, or Cognitive Science.
• Google Cloud Professional Machine Learning Engineer certification and/or specialized certifications in multi-agent systems/autonomous reasoning.
• 3+ years working with distributed caching technologies.
• Experience provisioning and configuring cloud platform resources at scale.
• Experience supporting consumer-facing digital or commerce environments.
• Proficiency with Google Workspace (Sheets, Docs, Slides, Gmail).

About Hansell Tierney:

Hansell Tierney is one of the premier staffing and recruiting companies in the Pacific Northwest. Launched in 2001, we are a woman-owned business that serves and staffs Northwest organizations by doing things the right way, not just the easiest way. Hansell Tierney partners with candidates and clients to match the best candidates with interesting local opportunities. We navigate every relationship with the highest level of discretion and service while holding ourselves accountable to our promises. Our business thrives on our deep understanding of the job market and our ability to skillfully tailor our recruitment process to meet our clients’ unique needs.

Location: El Segundo, Hybrid (in office Monday, Tuesday, Thursday) 

Pay: Competitive 100k - 200k Depending of Experience   

About Us:

At Ocra Brands, we're all about blending cutting-edge technology with business innovation. We're looking for passionate, sharp minds ready to dive deep and accelerate our digital transformation with AI, tech, tracking solutions, and software development

About the Role:

You will be our AI implementation champion—integrating AI tools and helping teams adopt them. You'll also ensure our tracking is top-notch across platforms like Google and Facebook Ads, and you’ll dive into Shopify and tools like Northbeam.

Key Responsibilities:

• Implement AI solutions across departments, helping colleagues use AI (e.g., claude code, automation) to enhance their work—whether they’re in CRO, SEO, or creative strategy.
• Work on high-level software development tasks and ensure our tech stack is robust and future-proof.
• Oversee tracking and analytics, ensuring seamless integration with tools like Google Ads, Facebook Ads, and Northbeam.
• Work closely with Shopify and ensure e-commerce tracking is accurate and optimized.
• Collaborate with cross-functional teams, supporting them in leveraging AI to improve their day-to-day tasks—from writing scripts to boosting creative efforts.

What We’re Looking For:

• Computer Science degree or equivalent from the top universities like or a clear demonstration of extra ordinary abilities in real work AI application and software development. We are looking for someone that not only have the ability to execute but also to understand drive the bigger picture strategy to AI/ Software integration across the whole company
• A great understanding of Software development and AI and how it related to business
• A proactive, problem-solving mindset. You ask “why” and never shy away from a challenge.
• Extreme sense of urgency—you move fast, innovate faster.
• Team player with a positive attitude, eager to grow and contribute to our culture.

Know more about us:

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• Design and implement automated workflows and AI agents for supply chain tasks.
• Conduct iterative testing and user acceptance testing with supply chain teams.
• Configure workflow logic, decision trees, automation sequences, and integration points for AI functionality.
• Develop hybrid solutions integrating analytics dashboards with AI workflows for process automation.
• Document workflow configurations, prompt patterns, and decisions in detail for non-technical user maintenance.

• Expertise in prompt engineering and AI platform management
• Proficiency in no-code/low-code workflow automation tools
• Deep understanding of AI agent training, context windows, model limitations, and hallucination mitigation.
• Basic technical understanding (APIs, data structures, integrations)

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible to bring life-changing therapies to patients worldwide.

The AI/ML organization at Takeda is building a team to transform how medicines are discovered. Our goal is to apply AI and machine learning across the entire drug discovery process, not just isolated steps, but as an integrated approach from target identification through development. This requires discernment: knowing which models and methods fit each problem, and the creativity to adapt when they don't. We work with foundational models, generative approaches, and autonomous systems, but the tools only matter when paired with people who understand the science deeply enough to use them well. Our team brings together computational scientists, biologists, engineers, and drug hunters. If you want to contribute your expertise to hard problems alongside colleagues with different perspectives, and help shape how AI delivers real impact in drug discovery, we'd like to hear from you.

Position Overview

We are seeking an innovative and dynamic AI/ML Research Senior Scientist with a passion for leveraging AI/ML in antibody discovery and design to join our Large Molecule AI/ML team. This role will be part of a multidisciplinary team focused on integrating advanced computational methods with cutting-edge experimental strategies to drive breakthrough discoveries in large molecule therapeutics and deepen our understanding of disease biology. The ideal candidate will have a strong background in computational biology, machine learning, and structural modeling and specifically with the application of AI/ML in biologics discovery.

Key Responsibilities

• Develop and implement state-of-the-art AI/ML methodologies for de novo antibody design and discovery, including fine-tuning protein language models and generative protein design.
• Develop, implement, and deploy advanced machine learning algorithms for the multi-objective optimization of antibodies, antigens, ADCs, and other biologics.
• Build tools to incorporate data from integrated Design-Predict-Make-Confirm cycles with automated experimental platforms generating quality data at scale needed for project-specific and foundational models.
• Innovate, develop, and apply predictive models for protein design and developability engineering, utilizing large-scale NGS, in vitro, in vivo and other proprietary in-house and external data sources.
• Manage and process large-scale biological datasets for model training and evaluation
• Stay abreast of advancements in NLP, ML, and generative AI to build novel tools that enhance therapeutic discovery and development.
• Collaborate with internal experts to optimize the computational discovery infrastructure, offering both individual and team-based innovative solutions.
• Communicate complex scientific ideas effectively to both technical and non-technical audiences, fostering collaboration across multidisciplinary teams.

Qualifications

• PhD degree in a scientific discipline (or equivalent) with 2+ years relevant experience, or MS with 8+ years relevant experience, or BS with 10+ years relevant experience
• Proven track record in developing machine learning models for chemical and biological data, including AI/ML-enabled molecular generation and affinity prediction.
• Demonstrated experience in modeling antibody/ antigen sequence, structure and interaction.
• Proficiency in programming languages such as Python and experience with cloud computing capabilities.
• Strong analytical and problem-solving skills, with demonstrated creativity and the ability to contribute individually and collaboratively.
• Versatile communicator who can elucidate complex ideas to non-specialists and commitment to continuous improvement and innovation.
• Demonstrated learning agility, and scientific curiosity while maintaining focus on driving greater impact in the face of uncertainty and change.
• Strong problem-solving aptitude and strategic thinking with an entrepreneurial mindset.

Preferred Qualifications & Skills:

• Experience developing or applying modern ML architectures for antibody design models (LLMs, diffusion models, flow-matching, Bayesian Optimization, GNNs, etc.)
• Experience designing de novo binders for specified targets and epitopes
• Experience analyzing NGS-derived antibody repertoires for sequence- and structure-based design
• Experience with molecular simulation and conformational analysis techniques

ADDITIONAL INFORMATION

• The position will be based in Cambridge, MA

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Worker Type

Worker Sub-Type

Time Type

Job Exempt

We are seeking a curious and motivated AI & Systems Operations Associate to join our team in Chicago. This is an entry-level opportunity ideal for a recent graduate or early-career professional who is excited about artificial intelligence and interested in how emerging technologies can improve the way businesses operate.You do not need to be an AI programmer or have a technical degree. What matters most is that you are analytical, tech-comfortable, and naturally curious about AI tools and new technologies. If you regularly explore tools like ChatGPT, enjoy learning new platforms, and like figuring out smarter ways to solve problems, this role could be a great fit.

You will work closely with internal teams to help support AI tools, operational systems, and technology-driven workflows.

Key Responsibilities

• Assist in supporting and maintaining internal operational systems and technology platforms
• Use AI tools to help improve workflows, research solutions, and increase efficiency
• Review and monitor AI-generated outputs to ensure accuracy and usefulness
• Help identify opportunities to streamline internal processes through technology
• Support the adoption and use of new tools and systems across teams
• Assist with documentation, testing, and improvement of technology-driven workflows
• Stay informed on emerging AI tools and technologies that may benefit the business

Qualifications

• Bachelor’s degree required (any field – Liberal Arts, Business, Technology, etc.)
• Strong curiosity about artificial intelligence and emerging technologies
• Comfortable using modern technology platforms and software tools
• Familiarity with AI tools such as ChatGPT or similar platforms
• Strong critical thinking and problem-solving abilities
• Organized, detail-oriented, and eager to learn
• Ability to work hybrid in Chicago (3 days per week in-office)

Nice to Have (Not Required)

• Exposure to workflow or contract management platforms such as Ironclad
• Internship or academic experience involving technology, research, or operations
• Interest in legal technology, legal operations, or business systems
• Basic understanding of automation, AI tools, or digital workflows

Role:

Join project teams across the U.S. as the on-site catalyst who turns AI ideas into working reality. Partnering with each project’s AI Champion (Project Manager or Superintendent), you’ll uncover pain points, redesign workflows, and deploy AI agents that cut down reporting, accelerate RFIs, simplify lookahead planning, progress updates, materials tracking, and more. When needed, you will develop user stories and coordinate development with the central AI Studio. You’ll help advance the vision of the “Construction Site of the Future,” showing how agentic AI will transform project operations.

Location: New Haven, Connecticut

Responsibilities:

• Opportunity hunting and workflow redesign – Lead Lean/Six Sigma discovery workshops; map value streams, assess process and data maturity, and log low-effort/high-impact AI use cases.
• Process and data maturity assessment – Evaluate each jobsite’s current workflows and underlying data; surface gaps that block AI adoption and develop phased improvement plans with Operations Excellence to establish the right process baseline before deploying agents.
• Assess the market solutions – Evaluate off-the-shelf and platform tools; launch pilots, measure impact, and scale wins.
• Rapid AI-agent builds – Convert user stories into production-ready agents in Copilot Studio / Power Apps/Automate, ChatGPT Enterprise, or code-first frameworks within days; wire them to Teams/SharePoint on the front end and Databricks Lakehouse or other sources on the back end.
• Enterprise-grade engineering & LLMOps – Build RAG pipelines backed by Delta tables, Unity Catalog, and Databricks Vector Search; automate infra with GitHub Actions / Posit; monitor latency, cost, adoption, and drift.
• Data integrations – Partner with Data Engineering to design and maintain ETL pipelines, API integrations, and event-driven connectors feeding RAG and agents.
• Cross-cloud orchestration – Blend OpenAI, Azure OpenAI, and AWS Bedrock behind secure custom connectors; package agents for seamless rollout.
• Change enablement – Train crews, gather feedback, iterate, and track adoption and ROI metrics; apply influence model principles to embed agents into daily routines and SOPs, and track behavior change KPIs.
• Stakeholder communication – Brief project leadership and clients on agent impact in clear business terms; contribute use cases and playbooks for “Construction Site of the Future.”
• Escalation & hand-off – Draft clear user stories, data specs, and acceptance criteria for any complex solution that requires the central AI Solution Engineers or Data Engineering / Data Science team to lean in.

Qualifications:

• 3+ years in AI engineering / full-stack data applications or data science, including 2+ years building production LLM/RAG solutions.
• Bachelor’s in CS, Engineering, Physics, or a related field; Master’s preferred.
• Prior hands-on work in construction or heavy process industries (manufacturing, oil & gas, chemicals) is a significant plus.
• Demonstrated process excellence background (Lean/Six Sigma Green Belt or equivalent) with experience diagnosing process and data gaps and supporting change management plans with Operations Excellence.
• Strong facilitation and communication skills.
• Hands-on expertise with Copilot Studio, Power Apps/Automate, custom connectors, and CoE Toolkit governance.
• Programming & data stack: Python, SQL, Databricks Lakehouse, vector stores.
• DevOps & IaC: GitHub Actions (or Azure DevOps) and Posit Workbench/Connect automation or comparable CI/CD tooling; strong Git/GitHub workflow discipline.
• Integration & ETL skills: Foundational understanding of ETL/ELT design, Airflow or Databricks Workflows, and REST/GraphQL API development; proven collaboration with Data Engineering on source-to-lake and lake-to-agent pipelines.
• Willing and able to travel and work on active jobsites.

By clicking the "Apply" button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda's Privacy Notice and Terms of Use. I further attest that all information I submit in my employment application is true to the best of my knowledge.

Job Description

At Takeda, we are a forward-looking, world-class R&D organization that unlocks innovation and delivers transformative therapies to patients. By focusing R&D efforts on three therapeutic areas and other targeted investments, we push the boundaries of what is possible to bring life-changing therapies to patients worldwide.

The AI/ML organization at Takeda is building a team to transform how medicines are discovered. Our goal is to apply AI and machine learning across the entire drug discovery process, not just isolated steps, but as an integrated approach from target identification through development. This requires discernment: knowing which models and methods fit each problem, and the creativity to adapt when they don't. We work with foundational models, generative approaches, and autonomous systems, but the tools only matter when paired with people who understand the science deeply enough to use them well. Our team brings together computational scientists, biologists, engineers, and drug hunters. If you want to contribute your expertise to hard problems alongside colleagues with different perspectives and help shape how AI delivers real impact in drug discovery, we'd like to hear from you.

Position Overview:

We are seeking Scientists to develop and deploy foundational AI models that will transform drug discovery across Takeda. As part of the AI/ML Foundation team, you will build large-scale models including large language models (LLMs), diffusion models, and multimodal architectures that integrate diverse data types—omics, biomedical imaging, protein 3D structures, and molecular representations. This role requires deep expertise in modern deep learning architectures combined with foundational knowledge of biology, chemistry, and disease biology to ensure models are scientifically grounded and impactful. You will train models from scratch, fine-tune pre-trained models for Takeda-specific applications, and deploy foundation model capabilities that accelerate discovery across all therapeutic platforms.

Accountabilities:

• Develop and train foundational AI models (LLMs, diffusion models, flow-matching architectures) for drug discovery applications, with capability to pre-train on large-scale scientific corpora and molecular datasets.
• Fine-tune and adapt pre-trained foundation models (protein language models, chemical LLMs, vision transformers) for Takeda-specific applications in target identification, disease modeling, and molecular design and discovery.
• Build multimodal foundation models integrating diverse data types including omics (genomics, transcriptomics, proteomics), biomedical imaging, protein 3D structures, and molecular representations.
• Apply and extend state-of-the-art approaches including graph neural networks, transformer-based protein language models, and multimodal learning frameworks.
• Apply domain expertise in biology, chemistry, and/or disease biology to guide model architecture decisions, training data curation, and evaluation strategies ensuring scientific validity.
• Implement state-of-the-art generative architectures (diffusion, score-based models, autoregressive transformers) for molecular generation, protein design, and multi-objective optimization.
• Collaborate with computational scientists across domains to deploy foundation models that address diverse discovery needs across small molecules, biologics, and emerging modalities.
• Stay current with advances in foundation models, generative AI, and multimodal learning; contribute to internal knowledge sharing and external publications.

Education & Requirements:

• PhD in Computer Science, Machine Learning, Computational Biology, Bioinformatics, or related field or MS with 6+ years relevant experience, or BS with 8+ years relevant experience
• Deep expertise in modern deep learning architectures including transformers, diffusion models, and/or generative models.
• Strong experience training large-scale models with proficiency in PyTorch and distributed training frameworks.
• Foundational knowledge of biology, chemistry, or disease biology sufficient to guide scientifically meaningful model development.
• Experience with at least one of: protein language models (ESM, ProtTrans), molecular generative models, or biomedical vision models.
• Experience with cloud computing (AWS, GCP) and GPU cluster training at scale.

Preferred:

• Experience building or fine-tuning foundation models in pharmaceutical or life sciences settings.
• Expertise in multimodal learning integrating text, images, and structured molecular data.
• Experience with omics data analysis (genomics, transcriptomics, proteomics) and knowledge graph
• Familiarity with protein structure prediction and 3D molecular representations.
• Publications in top-tier ML venues (NeurIPS, ICML, ICLR) or computational biology journals.
• Experience with model compression, efficient inference, or production deployment of large models.
• Strong background in large-scale data integration and multimodal modeling for biological systems.
• Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn); familiarity with Unix tools.
• Excellent collaboration and communication skills.

ADDITIONAL INFORMATION

• The position will be based in Cambridge, MA

Takeda Compensation and Benefits Summary

We understand compensation is an important factor as you consider the next step in your career. We are committed to equitable pay for all employees, and we strive to be more transparent with our pay practices.

For Location:

U.S. Base Salary Range:

U.S. based employees may be eligible for short-term and/ or long-term incentives. U.S. based employees may be eligible to participate in medical, dental, vision insurance, a 401(k) plan and company match, short-term and long-term disability coverage, basic life insurance, a tuition reimbursement program, paid volunteer time off, company holidays, and well-being benefits, among others. U.S. based employees are also eligible to receive, per calendar year, up to 80 hours of sick time, and new hires are eligible to accrue up to 120 hours of paid vacation.

EEO Statement

Takeda is proud in its commitment to creating a diverse workforce and providing equal employment opportunities to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, gender expression, parental status, national origin, age, disability, citizenship status, genetic information or characteristics, marital status, status as a Vietnam era veteran, special disabled veteran, or other protected veteran in accordance with applicable federal, state and local laws, and any other characteristic protected by law.

Locations

Worker Type

Worker Sub-Type

Time Type

Job Exempt

Location: Seattle (in-person)

Salary: $70,000–$110,000 depending on experience

Nimbus AI builds the fastest way for companies to create, train, and resell branded conversational and workflow agents. Our platform automates data capture, optimization, and deployment so teams can transform conversations and workflows into continuously improving, revenue-generating AI products.

We're hiring a QA Manager to build and lead the quality assurance function for Nimbus's agentic AI systems. You'll establish testing frameworks, develop evaluation criteria, and ensure our conversational agents and workflow automations perform reliably across all customer deployments. You'll work cross-functionally with product, engineering, and customer teams to catch edge cases, validate model behavior, and maintain the quality standards that make Nimbus agents trustworthy at scale.

This role is perfect for someone who loves building QA processes from the ground up, has a sharp eye for AI-specific failure modes, and can translate ambiguous agent behaviors into concrete test cases and quality metrics.

• QA strategy & framework development for conversational agents, workflow automations, and partner-specific models across multiple verticals.
• Test planning and execution—designing test cases, evaluation rubrics, regression suites, and automated testing pipelines for agent behavior.
• Quality metrics and monitoring to track agent accuracy, consistency, guardrail effectiveness, and performance degradation over time.
• Cross-functional collaboration with prompt engineers, product, and engineering teams to identify, document, and resolve quality issues.
• Agent validation processes to ensure new releases, prompt changes, and training updates maintain reliability standards.
• Team building and leadership as we scale—hiring, mentoring, and growing the QA function.

• 5+ years of QA experience, with at least 2 years in a management or lead role.
• Experience testing AI/ML products, LLM applications, or conversational systems—you understand non-deterministic behavior and how to test it.
• Strong analytical skills—comfortable evaluating agent outputs, identifying patterns in failures, and defining measurable quality standards.
• Ability to build testing frameworks from scratch, including test case libraries, evaluation criteria, and automation strategies.
• Experience with technical testing tools (APIs, JSON, test automation frameworks, monitoring systems).
• Excellent communication skills—you can clearly document bugs, write test plans, and explain quality issues to technical and non-technical stakeholders.
• Leadership experience building or managing QA teams, processes, and culture.

• Build the QA function from the ground up—define how quality works for agentic AI at scale.
• Be part of a small, fast team where your quality standards will directly impact hundreds of deployed agents.
• Work with cutting-edge LLMs and agentic systems—testing challenges that don't exist anywhere else yet.
• Grow into a senior leadership role as our platform, customer base, and team expand.

AI Trainer for Clinical Healthcare Research

Pay: $40-60/hr

Location: New York, NY

U.S. Citizens or GC Holders Only; No Visa Sponsorship

No relocation; Local Candidates Only

No c2c/third parties

Responsibilities:

• Train, fine-tune, and evaluate clinical AI models using real-world healthcare data
• Develop gold-standard evaluation benchmarks for medical AI systems
• Identify model biases, hallucinations, and unsafe outputs in clinical contexts
• Collaborate with physicians, nurses, and specialists to validate AI outputs
• Create feedback loops to continuously improve model performance
• Ensure compliance with HIPAA and healthcare data privacy standards
• Support deployment teams in validating AI systems prior to clinical rollout
• Contribute to documentation for regulatory review and quality assurance

Qualifications:

Required

• Clinical background (RN, MD, DO, PA, NP, PharmD, or equivalent healthcare credential) OR advanced degree in healthcare informatics, biomedical sciences, or related field
• 2+ years of clinical experience or healthcare operations experience
• Familiarity with electronic health record (EHR) systems
• Strong understanding of clinical documentation standards and terminology (ICD-10, CPT, SNOMED, etc.)
• Ability to critically evaluate medical content for accuracy and safety
• Strong written communication skills

Preferred

• Experience working with AI/ML systems or healthcare analytics
• Background in clinical quality improvement or patient safety
• Knowledge of regulatory frameworks (HIPAA, FDA software as a medical device guidance)
• Experience in data annotation, model evaluation, or prompt engineering
• Familiarity with LLMs and generative AI systems

Company Description

Edensign is building the future of AI-powered visual and spatial engine. Backed by the Harvard Innovation Labs, we’re creating next-generation intelligent systems that merge generative AI, 3D understanding, and spatial intelligence to transform how real-world spaces are visualized, staged, and experienced.

Contact Email:

Role Description

Full-time | Preference for Boston based candidates

We’re looking for a senior technical leader to drive the development of our core AI engine. The ideal candidate has deep experience training large generative models, including diffusion, 3D reconstruction networks, multimodal, VLM architectures. In this role, you will spearhead model training pipelines, R&D experiments, data strategy, and foundational architecture decisions.

This is an opportunity to help build the next generation of spatial AI - from multi-view consistency to 2D-to-3D-to-2D transformation and advanced scene understanding.

Key Responsibilities

• Design, train, and optimize cutting-edge generative models, including diffusion, 3D reconstruction, and multimodal/VLM architectures
• Build and manage scalable training pipelines, data curation workflows, and experiment tracking
• Lead research experiments, benchmarking, and exploration of new modeling techniques
• Architect the evolution of our spatial AI stack—from prototyping new ideas to deploying production-ready models
• Collaborate with engineering and product teams to integrate AI capabilities seamlessly into real-world workflows
• Make strategic decisions around infrastructure, GPU utilization, model efficiency, and training optimization
• Contribute to Edensign’s long-term technical roadmap and innovation direction

Qualifications

• Strong expertise in training generative models (diffusion, GANs, 3D generative models, or scene-reconstruction networks)
• Deep background in Computer Vision, Computer Graphics, 3D geometry, NeRF-like architectures, or multi-view learning
• Familiarity with node-based generative tools (e.g., ComfyUI) is a plus
• Experience with VLMs, multimodal models, grounding, or spatial reasoning is highly valuable
• Proficiency in Python and modern ML frameworks
• Hands-on experience with distributed training, GPU optimization, and large-scale experiment management
• Ability to work independently and lead technical direction in a fast-paced startup environment
• Strong analytical, problem-solving, and system design skills
• Excellent communication and collaboration skills
• Master’s or PhD in Computer Science, AI/ML, Computer Vision, or a related field
• Experience in real estate, architecture, spatial design, or spatial computing is a bonus
• Proficiency in Mandarin is preferred

Location: Dallas, Texas, United States

We are looking for a senior business development leader to drive growth in the rapidly expanding AI Data Center construction and infrastructure market. This role is ideal for a strategic professional with strong industry relationships and a proven track record of winning large-scale AI / hyperscale data center projects.

The successful candidate will lead business development initiatives, build strategic partnerships, and secure high-value projects within the AI and hyperscale data center ecosystem.

Key Responsibilities

• Lead business development strategy for AI and hyperscale data center construction projects

• Identify and secure new opportunities with AI companies, hyperscalers, developers, and data center operators

• Build and maintain executive-level relationships with key stakeholders and decision-makers

• Manage the full sales lifecycle from lead generation to contract closure

• Collaborate with internal teams including engineering, construction, and project management

• Track industry trends, emerging technologies, and market opportunities in AI infrastructure

Requirements

• 10+ years of experience in business development, sales, or strategic partnerships

• Strong background in data center development, construction, or mission-critical infrastructure

• Demonstrated success in securing large-scale data center or AI infrastructure projects

• Established network with hyperscalers, AI companies, developers, or colocation providers

• Excellent leadership, negotiation, and relationship management skills

About Us:

Astiva Health, Inc., located in Orange, CA is a premier health plan provider specializing in Medicare and HMO services. With a focus on delivering comprehensive care tailored to the needs of our diverse community, we prioritize accessibility, affordability, and quality in all aspects of our services. Join us in our mission to transform healthcare delivery and make a meaningful difference in the lives of our members.

SUMMARY:

We are seeking a skilled and adaptable Junior AI/ML Engineer to join our fast-moving team building impactful AI solutions in healthcare. Our work focuses on extracting and interpreting data from unstructured medical documents, improving clinical coding accuracy, streamlining administrative processes, and enhancing patient outreach.

Projects will evolve rapidly, from fine-tuning large language models (LLMs) on specialized medical PDFs, to optimizing OCR pipelines in Azure, and new challenges emerge regularly. This role suits someone who thrives in ambiguity, enjoys hands-on model development, and wants to directly influence healthcare delivery through applied AI/ML.

ESSENTIAL DUTIES AND RESPONSIBILITIES include the following:

• Design, fine-tune, and optimize large language models (LLMs) and multimodal models for healthcare-specific NLP tasks, such as information extraction, classification, and summarization from clinical documents (e.g., medical charts, patient files, scanned forms).
• Develop and improve document understanding pipelines, including fine-tuning OCR / layout-aware models (especially in cloud environments like Azure AI, Azure Foundry) to handle real-world variability in medical forms, handwriting, and scanned PDFs.
• Build and iterate on end-to-end ML solutions that transform unstructured healthcare data into structured, actionable insights
• Collaborate closely with clinicians, product managers, data annotators, and engineers to define problems, curate/annotate datasets, evaluate model performance against clinical and business metrics, and iterate quickly.
• Deploy models into production environments (cloud-based inference, batch processing, or API endpoints) with attention to latency, cost, scalability, and healthcare compliance considerations (HIPAA, data privacy).
• Stay current with advancements in LLMs, vision-language models, efficient fine-tuning techniques (LoRA/QLoRA, PEFT), RAG, multimodal AI, and domain-specific healthcare AI research.
• Contribute to a culture of rapid prototyping, rigorous evaluation, and continuous improvement in a dynamic project landscape where priorities can shift based on new opportunities or stakeholder needs.
• Other duties as assigned

REQUIRED TECHNICAL SKILLS:

• Proficiency in Python and familiarity with common ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
• Experience applying NLP techniques to unstructured text
• Hands-on experience working with LLMs, including:
• Prompt design and iteration
• Using pre-trained models for classification or extraction tasks
• Foundational understanding of model fine-tuning, such as:
• Fine-tuning transformer models or LLMs for classification or information extraction
• Adapting existing training scripts or examples to new datasets
• Familiarity with model evaluation metrics (precision, recall, F1) and basic error analysis
• Experience working with labeled datasets and annotation outputs, including reviewing label quality
• Understanding of common ML problem types, including binary and multi-label classification
• Awareness of model bias, label noise, and false positives, with the ability to discuss tradeoffs and mitigation strategies
• Basic understanding of production ML workflows (versioning, reproducibility, monitoring concepts)

OTHER SKILLS and ABILITIES:

• Hands-on fine-tuning experience with LLMs (e.g., Hugging Face, OpenAI fine-tuning, Azure Foundry), even if limited to small-scale or academic projects
• Exposure to cloud ML platforms (Azure ML, AWS SageMaker, or GCP)
• Familiarity with RAG architectures and retrieval-based grounding
• Experience with NLP libraries (spaCy, Hugging Face Transformers, NLTK)
• Introductory experience with weak supervision or noisy-label learning
• Interest in healthcare or biomedical NLP
• Curiosity about knowledge graphs, ontologies, or structured prediction
• Familiarity with secure data handling practices
• Willingness and ability to learn workflows for sensitive or regulated data (e.g., HIPAA-covered healthcare data), including privacy-aware data handling and secure ML workflows

EXPERIENCE:

• Bachelor’s Degree in related field
• 1–2 years of experience in machine learning, applied NLP, or software engineering
• Demonstrated some experience training or fine-tuning ML models, not just using APIs
• Ability to collaborate with senior engineers and domain experts and incorporate feedback

BENEFITS:

• 401(k)
• Dental Insurance
• Health Insurance
• Life Insurance
• Vision Insurance
• Paid Time Off
• Free catered lunches

Profitmind is building the intelligence behind how retailers make pricing and merchandising decisions. Today, many of these decisions are still driven by spreadsheets, rigid rules, and manual judgment, even at the largest brands.

Our platform turns complex data such as sales, inventory, and competitive signals into clear, explainable recommendations merchants can trust. Our platform focuses on impact, helping retailers improve margin, inventory health, and decision quality at scale. 

Based in Pittsburgh, Profitmind is backed by a recent strategic investment from Accenture, and scaling its agentic AI platform to power decision-making for some of the world’s largest retailers.

About the role:

We’re looking for a multi-disciplinary AI Engineer to design, implement, and deploy LLM-driven agents with strong backend and front-end integration. You’ll be leading efforts across LLM agent design, prompting, fine-tuning, and MLOps, while building real-world, production-grade applications with modern web technologies.

The ideal candidate combines a strong foundation in Python and AI with practical experience in agent frameworks like LangGraph, PydanticAI, and Google ADK, as well as FastAPI and front-end development.

What you’ll do:

LLM Agents & Prompt Engineering

• Architect and implement LLM agents using frameworks like LangGraph, PydanticAI, and Google ADK.
• Build composable, tool-augmented reasoning chains (e.g., RAG, CoT, ReAct, planner-executor).
• Integrate vector databases (e.g., FAISS, Pinecone, pgvector) and knowledge graphs (Neo4j) to support retrieval-augmented generation (RAG) and long-term chatbot memory.
• Design and maintain high-quality prompt strategies for robustness and reliability.

FastAPI, Model Context Protocol (MCP) & Backend

• Develop and maintain scalable APIs using FastAPI, supporting synchronous and asynchronous agent execution.
• Integrate Model Context Protocol (MCP) to enable secure and structured access to external data and tools within agent workflows.
• Implement state tracking, context-aware input dispatch, and modular plugin integration within the control plane.

Evaluation, Testing & Observability

• Build unit and behavioral tests for agents, tools, and workflows.
• Develop tooling for trace analysis, agent state debugging, and hallucination tracking.
• Compare and benchmark agent orchestration frameworks for trade-offs in speed, reliability, and usability.

Model Fine-Tuning & MLOps

• Fine-tune models using LoRA, QLoRA, or full fine-tuning pipelines.
• Integrate, deploy, and monitor models in production using cloud providers.
• Set up agent logging, observability dashboards, and recovery workflows.

Front-End & UX

• Familiar with React, TypeScript, Next.js, or similar frameworks
• Understanding of front-end and back-end integration for AI tools
• Ability to build basic dashboards or agent interfaces
• Integrate agents into interfaces
• Speak the language of UI 

What we’re looking for:

• 3+ years experience with Python in ML/AI systems and PyTorch or Tensorflow
• 1+ years experience with LLM agent development, prompt engineering, and frameworks like
• LangGraph, PydanticAI, and Google ADK.
• Experience with fine-tuning LLMs.
• Familiarity using vector stores like ChromaDB, Weaviate, or pgvector.
• Production experience with FastAPI, Docker, and MLOps
• Expert in Agentic Coding IDEs (Windsurf, Cursor or Claude Code)
• Bachelor’s or Master's degree in computer science

Nice to have:

• Open-source contributions to LLM/agent tooling
• Knowledge of async programming, websockets, and streaming APIs

What we offer:

• Competitive compensation and equity
• Comprehensive benefits including medical, dental, vision, etc.
• Unlimited and flexible PTO

Management Consultant – Life Sciences AI and Project Management New York City (Hybrid)

We are seeking an experienced management Consultant (manager level) to support a major pharmaceutical client in enhancing their AI capability and executing a number of enterprise-level initiatives. This hybrid role requires periodic on-site presence (1-2 days per week) in Hudson Yards alongside remote flexibility, with direct engagement at the senior stakeholder level. Initial project is set for 2 years, with planned rollover to other projects with the same client thereafter. Excellent work/life balance (client hours and primarily remote) and exposure to senior decision-makers in a rapidly evolving area.

Key Responsibilities

• Oversee enterprise-level workstreams within a top-10 pharma
• Work closely with senior stakeholders to design and implement plans for integrating AI into operations
• Structure and manage cross-functional initiatives, tracking milestones, managing risks, and driving accountability across teams
• Develop high-quality executive deliverables including presentations, roadmaps, and status reporting materials
• Facilitate working sessions and stakeholder interviews; synthesize findings into clear, actionable recommendations

Required Qualifications

• Must be located in commutable distance to New York, New York, United States
• 7+ years of consulting experience, with demonstrated focus in pharmaceutical, life sciences, or healthcare compliance at the manager level
• Background at a major consultancy (e.g., Deloitte, PwC, Accenture, BCG, or equivalent) required
• Working knowledge of AI tools and their practical application in regulated industry settings
• Exceptional proficiency with Microsoft Office suite, particularly PowerPoint, Excel, and Teams
• Strong executive communication and presentation skills; comfort engaging C-suite and senior leadership audiences
• Proven ability to manage multiple workstreams independently in fast-moving, ambiguous environments

Ideal Candidate A strategic thinker and disciplined project manager who brings a robust consulting skillset and knowledge and interest related to life sciences and AI.

Compensation Very highly competitive; commensurate with experience.

Founding Sales Partner (Commission-Based) | High-Ticket Software & AI

Location: Hybrid. Primarily remote, with the option to connect in person.

Employment Type: Part-Time / Contract (10–20 hours/week)

Compensation: 10% Uncapped Commission ($10k+ payout per $100k contract)

The Opportunity

Platinum Programming is a boutique software development firm building the next generation of custom web, app, and AI solutions. We move fast, build with modern stacks (Next.js, React), and solve complex problems for ambitious startups and established businesses.

We are looking for our first Founding Sales Partner to build and own our sales engine. This is a high-upside, entrepreneurial role designed for a closer who wants to dominate the tech and AI space without being tied to a 9-to-5 desk. No prior software or engineering experience is required—we provide the technical expertise; you provide the relationship-building and closing power.

Compensation & Growth

This is a purely commission-based role at the outset, designed to reward high performers with immediate, significant payouts.

• 10% Flat Commission: On all closed deals (Example: A $100k contract = $10,000 payout).
• Uncapped Potential: No ceilings on deal size or volume.
• The Path to Full-Time: We are looking for a long-term partner. High performers will have a clear, priority pathway to transition into a salaried Director of Sales role with benefits as we scale.

We Fuel Your Success (The Toolkit)

We don’t expect you to pay out of pocket to do your job. We provide the full "Sales Stack" needed to hunt and close:

• LinkedIn Premium / Sales Navigator: Full access for lead prospecting.
• Premium Business Data: Access to databases (Apollo, etc.) for verified emails and direct dials.
• Lead Generation: We provide the tools; you provide the outreach.
• Collateral: Professional slide decks, case studies, and technical white papers.

What You’ll Do

• Own the Funnel: Build and manage the full sales cycle—from cold outreach (LinkedIn, Email, Phone) to qualified discovery.
• Local Networking: Represent Platinum Programming at Utah tech gatherings (Silicon Slopes, local meetups, and industry conferences).
• Consultative Selling: Engage with CEOs, Founders, and VPs to understand their digital transformation needs.
• Partner with Devs: You aren’t alone. You’ll collaborate closely with our technical team to craft proposals and ensure project feasibility.
• Close High-Ticket Deals: Guide prospects through discovery, proposal, negotiation, and the final handshake on $100k–$200k+ projects.

Who You Are

• A Proven Closer: You have a track record of selling high-value services (SaaS, Real Estate, Consulting, B2B).
• Entrepreneurial Mindset: You don’t need a manager to tell you to pick up the phone. You are self-motivated and thrive in a “startup” environment.
• Master Communicator: You can translate complex business needs into clear solutions over Zoom, email, or a coffee in Lehi.
• Utah Resident: Needed for in-person strategy sessions and local networking.

Why Join Us?

• Flexibility: Work 10–20 hours per week on your own schedule. Perfect for fractional pros or those building a portfolio.
• Founder Support: You will work directly with the technical founders. We join your discovery calls to handle the “tech heavy lifting.”
• Modern Portfolio: Sell cutting-edge AI integrations and high-performance apps that businesses actually need.
• Full Toolkit: We provide the scripts, lead lists, CRM access, and training to ensure you hit the ground running.

How to Apply

If you are ready to build the sales foundation of a growing tech firm, apply directly on our site: include:

A link to your LinkedIn profile.

A brief note on your most impressive sales win (size of deal, how you closed it, or quota surpassed).

CommanderAI is building the go-to revenue engine for the $100B+ waste and recycling industry. We help haulers find, win, and keep more business using AI-driven data, automation, and a sales workflow built specifically for this market.

We’re hiring a high-volume Account Executive (AE) with uncapped upside to take qualified opportunities from our SDR team and turn them into long-term, high-value customers. If you love running tight sales cycles, delivering sharp demos, and closing net-new logos in an industry that’s just starting to adopt modern tech, keep reading.

What you’ll do

• Own the close: Take qualified meetings and opportunities from SDRs and drive them from discovery through demo, proposal, and signed agreement.

• Run high-impact discovery: Quickly understand a hauler’s line of business and current sales process so you can map CommanderAI to real business outcomes.

• Deliver killer demos: Lead a high velocity sales cycle with tailored demos that show owners and sales leaders how CommanderAI helps them find and win more customers.

• Master High-Velocity Sales: You will be a closing machine. Expect to handle a high volume of inbound demos daily (4-6+/day @ 20-30 min ea). You are ruthless with your time management, quick on your feet, and able to move haulers from "Hello" to "Signed" in 30 days or less.

• Build and manage pipeline: Maintain super fast sales cycles in a clean, accurate pipeline, including deal stages, close dates, and forecast in our CRM.

• Quote and negotiate: Create pricing proposals and quotes, handle objections, and negotiate terms that align value, margin, and long-term partnership.

• Collaborate to win: Partner closely with SDRs on handoffs and follow-through, and with onboarding / product to ensure a smooth go-live and strong early usage.

• Be the trusted advisor: Act as a consultative partner to haulers - not a feature pitcher - helping them modernize their sales process with AI.

• Bring the market back inside: Relay feedback, objections, and feature requests from prospects to leadership and product to help shape the roadmap.

What you’ve done

• Experience: 3+ years in a quota-carrying Account Executive or closing role in B2B, ideally SaaS. Experience selling into SMB / mid-market is a plus.

• Closing track record: Consistently hit or exceeded quota in a closing role, with clear examples of managing a structured sales process from discovery to close.

• Industry familiarity (nice-to-have): Experience selling to waste & recycling, field services, logistics, construction, or other operations-heavy industries.

• Strong communicator: Comfortable presenting to owners, GMs, and sales teams. You can simplify complex tech and keep the conversation focused on ROI and outcomes.

• Process & CRM minded: You live in a CRM, keep your pipeline clean, and can forecast your business with reasonable accuracy.

• Self-starter: You don’t need hand-holding. You show up prepared, run your territory like a business, and find ways to create momentum.

• Comfort with AI & software: You don’t have to code, but you should be comfortable demoing SaaS and talking about AI in practical, non-hype terms.

Why CommanderAI

• Compensation: Competitive base salary + uncapped commission and fast-payouts.
• Structure: Clear quota, transparent comp plan, and no cap on what you can earn if you keep closing.
• Category momentum: Waste and recycling is modernizing fast, and there is no dominant sales platform in the space yet. You’ll help define it.
• Real-world impact: You’re not selling another dashboard for marketers. You’re helping haulers win business, grow routes, and create jobs.
• Ground-floor seat: Join a tight, high-caliber team early, help shape the sales playbook, and grow into senior AE / sales leadership as we scale.

Equal Opportunity

CommanderAI is an equal opportunity employer and values diversity. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, or disability.