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Senior Applied AI Scientist

Fully Remote - HQ in New York, New York

$190,000-210,000 base salary + equity

THE COMPANY

Harnham is partnering with an innovative health-tech startup building patient-focused agentic AI, multimodal computer vision and LLM applications to advance capabilities in medical claims and medical imaging in hospitals. The AI science team builds scalable, data-driven solutions that personalize user experiences and equip care providers with actionable insights, all while working with large-scale infrastructure and diverse technologies.

THE ROLE

• You will be responsible for computer vision and multimodal model research, building and development for the company's agentic AI product across imaging centers and hospitals
• You will report directly to senior leadership and work closely on technical direction
• Own applied AI research and quickly build into production, particularly focusing on novel AI, computer vision and LLM applications
• You will directly work with production team on implement and design code and build out to production using various machine learning, imaging and LLM techniques, owning machine learning modeling
• You will play an integral role of building out the AI team and scaling out its product
• Act as a thought leader role for AI across the business, mentoring junior team members

YOUR SKILLS AND EXPERIENCE

The successful Senior Applied AI Scientist will likely have the following skills and experience:

• 5+ years of commercial experience preferred with a focus on applied machine learning and computer vision research, building production-grade models with NLP and LLMs ideally with voice, image and multi-modal systems
• Experience working in a scaling startup is preferred
• Expertise in Python (TensorFlow, PyTorch) for production-grade work
• Commercial experience building novel AI platforms with large datasets
• History of working with and managing real-time AI applications in production settings
• Cloud experience in AWS, Azure or GCP
• DevOps exposure with CI/CD pipelines preferred
• History of working on models from concept to production / end-to-end / 0-1
• Applied research background in a commercial setting required
• Publication and/or patent history highly preferred
• Experience in settings wearing multiple hats
• Domain experience in healthcare, health-tech, med-tech or similar a plus; EHR, EMR, claims, HEOR or other medical data exposure highly preferred
• History of partnering with non-technical stakeholders required
• Experience owning projects
• PhD degree in Medical Imaging, Computer Science, Biomedical Imaging or similar

THE BENEFITS

A competitive base salary of $190,000-210,000 + benefits + equity

HOW TO APPLY

Please register your interest by sending your résumé to Tim Jonas via the Apply link on this page.

KEYWORDS

Machine Learning | AI | Artificial Intelligence | Technology | Applied Research | Health-tech | Healthcare | Medical | Startup | Deployment | Production | LLMs | LLM | Large Language Models | GenAI | Gen AI | Generative AI | Voice Bots | Chatbots | Natural Language Processing | EHR | Electronic Health | Electronic Medical | HEOR | Claims Data | Patient | Hospital | Docker | Kubernetes | Weights & Biases | PyTorch | TensorFlow | Publications | Patents | Computer Vision | Medical Imaging | MRI | Multimodal

Job Summary
HellermannTyton North America (HT NA) is accelerating the use of Artificial Intelligence to unlock capacity, improve quality, and fuel growth across North America. As the AI Program Manager, you will build and run a program of AI initiatives that create efficiencies by automating repetitive tasks and removing process waste. You will partner with Operations, Sales, Marketing, IT, HR, and Finance to select the right problems, deliver measurable outcomes quickly, and scale wins across plant sites to increase revenue, reduce cost, and eliminate waste. This will be achieved while maintaining HellermannTyton's Quality and EHS certifications by supporting all corporate policies, procedures, work instructions, and required documentation.

What You'll Do

Opportunity Discovery

• 
  
  
• Conduct stakeholder interviews to capture business objectives and constraints; translate high-level goals into clear, actionable AI project requirements.
  
  
• Build simple business cases with the respective departments; baseline current performance, and quantify benefits
  
  

Program Management

• 
  
  
• Work with Business Stakeholders to prioritize initiatives by value, impact, labor hour avoidance, and risk mitigation.
  
  
• Prioritize AI program and project roadmap into short, iterative deliverables; prioritize delivery based on business impact and feasibility.
  
  
• Run stage-gated delivery (scope pilot scale) aligned to HellermannTyton COE project governance; set decision forums, risk controls, and incremental results.
  
  
• Work with Business and IT to develop data and IT infrastructure and tools to support AI program roadmap.
  
  

Delivery

• 
  
  
• Ensure ownership of agents and AI workflows are transitioned to business stakeholders within the business.
  
  
• Engage with change management to ensure AI projects are accepted, and AI becomes integrated into processes such that AI becomes "the way we work."
  
  
• Make value visible and auditable. Track and report on program benefit metrics such as savings, improved experience, reduced waste, efficiency improvements, etc.
  
  
• Share AI knowledge to upskill the organization. Coach stakeholders to see AI use cases in the processes.
  
  

Governance

• 
  
  
• Partner with Legal/HR on data privacy and AI use policies.
  
  
• Ensure solutions comply with IT corporate cybersecurity and risk guidelines.
  
  

Success in this role will require:

• 
  
  
• Collaboration & Communication
  
  
• Adaptability
  
  
• Problem Solving
  
  
• Analytical Thinking
  
  
• Business Acumen
  
  

What You'll Bring

• 
  
  
• Bachelor's degree in Project/Program Management, Engineering, Manufacturing, Computer Science, Data/Analytics, or related field.
  
  
• 3+ years leading data/AI/automation programs with manufacturing operations; proven track record delivering hard dollar benefits and labor hour avoidance.
  
  
• Mastery of program management (business cases, roadmaps, stage gates, financials).
  
  
• Excellent stakeholder communication and leadership across Operations, Sales, Marketing, IT, HR, and Finance.
  
  

Preferred Qualifications

• 
  
  
• Background manufacturing or associated environments.
  
  
• Lean / Six Sigma certification; experience embedding AI within continuous improvement programs.
  
  
• Experience with AI Tools (MS CoPilot Studio, MS Fabric, MS Azure Foundry)
  
  

By applying for a position with HellermannTyton, you understand that should you be made an offer, it will be contingent on your undergoing and successfully completing a background check through the use of our 3rd party supplier. Background checks may include some or all of the following based on the nature of the position: SSN/SIN validation, education verification, employment verification, criminal check, driving history, and drug test. You will be notified during the hiring process of which checks are required by the position.

HellermannTyton Corporation is an Equal Opportunity Employer and does not discriminate against any employee or applicant for employment because of race, color, sex, age, national origin, religion, sexual orientation, gender identity, status as a veteran, and basis of disability or any other federal, state or local protected class.

We’re hiring a B2B SaaS Account Executive to drive growth for our AI-powered solutions used by growing and enterprise businesses.

As an Account Executive at Commercient, you’ll own the full sales cycle for our AI automation and chatbot solutions, from prospecting and demos to closing complex B2B SaaS deals. You’ll work directly with customers to understand real business problems and translate cutting-edge AI—LLMs, intelligent automation, and ERP–CRM integrations—into practical, high-impact outcomes. This is a SaaS sales role for someone excited to sell sophisticated AI technology, engage senior stakeholders, and help shape the next generation of AI-driven sales motions.

At Commercient, you’ll own the full sales cycle, working directly with decision-makers to understand business challenges and position high-impact solutions that combine ERP, CRM, and AI capabilities.

Location: Atlanta (Hybrid)/US (remote)

What You’ll Do

As our Sales Representative, you’ll be on the front lines driving our growth:

• Prospect, pitch, and close deals for our AI technology solution such as our chatbot
• Build and nurture strong client relationships with Salesforce, HubSpot, Zoho, etc.
• Represent Commercient at meetings, demos, and events across the US
• Gather insights from the market to help shape our product and sales strategy
• Hit and exceed sales targets while growing your career in a fast-moving company
• Travel to several conferences per year in the US

Who You Are

• Sales hunter with a passion for building relationships and closing deals
• Energetic, ambitious, and motivated by results
• AI enthusiast who likes to learn about AI and stays current with the trends
• Comfortable meeting clients and thriving in a dynamic, less-structured environment
• Bachelor’s degree or equivalent experience in Sales, Business Development, or related fields (optional if you have killer sales results!)
• 3-7 years of experience in SaaS or AI solution sales (ERP, CRM, or automation experience strongly preferred)
• Familiarity with Salesforce, HubSpot, or ERP ecosystems
• Understanding of AI chatbots, RAG systems, or natural language interfaces (bonus if you can explain GPT, embeddings, or vector databases in plain English)
• Consultative, high-EQ selling style with technical curiosity
• Comfortable engaging at C-level and VP-level
• Self-starter with strong pipeline discipline and storytelling ability
• Excited about shaping a next-generation AI sales motion
• Experience with any Chatbot or LLM tech stack: Google Gemini, Google AI Studio, Open AI, Liveperson, Drift chat, Microsoft Copilot, Agents, Agentforce, HubSpot AI, Support desk or Helpdesk AI assistants, Slack AI assistants, etc.
• Comfortable working independently in a remote team environment
• Applicants must have near-native English proficiency. A short written and verbal English evaluation will be part of the selection process.

Not for you if: you dislike rejection or ambitious goals.

Why Join Us?

• Be a key player in our expansion — your impact is direct and visible
• Work closely with founders and an international team
• Learn and grow in a tech-driven, fast-moving environment
• We have an engaging, collaborative culture focused on succeeding together

Compensation & Perks

• Competitive base starting at $55k (based on experience) + commission — uncapped, performance-driven commissions per annual On Target Earnings (OTE)
• Our compensation plan creates a space for you to be in control of what you make. The base is a great start, but uncapped commission is accessible your entire career with us (your base and commission will increase as you grow with the company).
• Comprehensive Benefits Package
• 401k program with generous company match
• PTO
• Hybrid role based in Atlanta, GA with fully remote option for US-based candidates

About Commercient

Commercient helps growing companies streamline Sales, Marketing, and Customer Service by seamlessly connecting ERP and CRM systems through our AI-driven integration platform. Over 50,000 users rely on Commercient SYNC daily to automate key business processes—sales, billing, invoicing, and payments—across top CRMs like Salesforce, HubSpot, and Microsoft Dynamics. We’re an innovative, global SaaS company with 20+ years of experience and customers in 1,000+ organizations worldwide.

Why Work With Us

• Work remotely with a diverse, supportive, and fun global team
• Be part of an innovative company that embraces cutting-edge technology
• Enjoy learning and development opportunities to grow your career
• Flexible work-life balance and an environment where ideas thrive

Ready to join an innovative team building the world’s leading ERP–CRM integration platform? Apply today and grow your career with Commercient.

Role:

The Technical Product Manager, Functional AI, will lead the definition and delivery of AI solutions that transform our core business functions, including Finance, HR, Legal, Marketing, and others. This role bridges functional expertise and technical execution—partnering with business leaders to identify opportunities, shaping requirements into scalable AI solutions, and ensuring adoption that delivers measurable value. The Technical Product Manager will collaborate closely with engineers and data teams to design, pilot, and scale solutions, while maintaining clear visibility into ROI and impact for leadership. Success in this role requires strong product management discipline, applied AI expertise, and the ability to translate complex technical concepts into business outcomes.

Responsibilities:

Product Management & Business Partnership:

• Lead discovery and scoping sessions with business stakeholders across corporate functions (Finance, HR, Marketing, etc.) to identify high-value AI opportunities.
• Build strong relationships with functional leaders to understand workflows, pain points, and success measures.
• Translate business requirements into clear technical requirements that guide design, engineering, and vendor evaluation.
• Drive user experience design by ensuring solutions are intuitive, accessible, and aligned with employee needs.
• Prepare clear documentation of requirements, workflows, and decision rationale to support transparent delivery.
• Lead Agile sprint planning, backlog grooming, and retrospectives to ensure timely and high-quality delivery of product features in collaboration with cross-functional teams.

AI Solution Design & Delivery Support:

• Partner with engineers to shape solution approaches, balancing build/buy/partner considerations.
• Contribute to solution architecture discussions, ensuring designs are scalable, secure, and compliant with standards.
• Collaborate closely with delivery teams to validate functionality against requirements, proactively evaluate feature effectiveness and accuracy, and resolve scope or design ambiguities to ensure product quality and alignment with user needs.
• Support testing, pilot deployment, and adoption efforts, incorporating user feedback into iterative improvements.
• Document and communicate lessons learned, value metrics, and impact stories to demonstrate business outcomes.

Value & Impact Measurement:

• Define success metrics and measurable outcomes for each AI initiative in partnership with business stakeholders.
• Work closely with the Data Analytics team to design and maintain value tracking reports and dashboards.
• Monitor adoption, efficiency gains, and ROI, and proactively identify areas for improvement.
• Present value realization updates to leadership, ensuring clear visibility into the business impact of AI solutions.

Qualifications:

• At least 5 years of experience in technical product management with a minimum of 2 years in AI-related products.
• Bachelor’s and Master’s in Computer Science, Physics, Engineering, or associated quantitative fields.
• Have proven experience and knowledge of corporate functions (Finance, HR, Legal, Marketing, etc.)
• Exceptional facilitation and communication skills—comfortable running discovery sessions, white-boarding with PMs, and demoing prototypes to senior leaders.
• Demonstrated product-management mindset: roadmap ownership, KPI definition, and budget/risk trade-off communication.
• Hands-on experience leading change initiatives and measuring adoption by teams.
• Strong analytical and problem-solving skills
• Excellent communication and collaboration skills
• Ability to articulate technical concepts to non-technical stakeholders
• Deep understanding of AI applications, tools, and methodologies
• Proven ability to apply AI/ML techniques (e.g., NLP, document intelligence, predictive modeling, generative AI) to solve business problems in corporate functions.
• Hands-on experience with modern AI/ML tools and platforms (e.g., OpenAI, Azure AI, AWS SageMaker, AWS Bedrock or similar).
• Familiarity with the latest trends in AI (e.g., agentic AI, multimodal models, RAG) and ability to evaluate their relevance for client use cases.

Key Responsibilities:

• Design and deploy observability frameworks leveraging tools such as Grafana, Dynatrace, Prometheus, ELK, Splunk, etc. Define best practices for monitoring, alerting, and visualization across hybrid and multi-cloud environments.
• Develop strategies for monitoring KPIs tied to business outcomes (e.g., sales performance, supply chain efficiency, customer experience).
• Collaborate with business and IT teams to identify key metrics and integrate them into dashboards and alerting systems.
• Implement AIOps solutions using industry-leading platforms like OpenAI, AWS Bedrock, Google Gemini, Anthropic, and similar technologies.
• Develop predictive analytics and anomaly detection models to proactively identify and resolve operational issues.
• Integrate observability tools with ITSM platforms and automation workflows. Enable automated root cause analysis and remediation using AI/ML models.
• Provide observability strategies for infrastructure (servers, storage, cloud), applications (microservices, APIs), and networks (LAN/WAN, SD-WAN). Collaborate with DevOps, SRE, and IT operations teams to ensure end-to-end visibility and reliability.
• Establish observability standards, KPIs, and SLAs for performance and availability. Ensure compliance with security and regulatory requirements in monitoring solutions.
• Develop scalable architecture using LLMs, agentic frameworks, and multi-modal AI technologies.
• Build AI-powered analytics platforms for IT operations analysis, anomaly detection, and predictive insights.
• Architect and deploy intelligent chatbots for IT support and self-service capabilities.
• Integrate AI solutions with existing IT operations tools and workflows.
• Implement automated remediation and root cause analysis using AI/ML models.

Qualifications:

• 10-13 years of relevant experience
• Hands-on experience with Grafana, Dynatrace, and other monitoring platforms.
• Practical experience implementing AI-based solutions for anomaly detection, predictive maintenance, and automated remediation. Familiarity with OpenAI, Bedrock, Gemini, Anthropic, or similar AI platforms.
• Strong understanding of infrastructure, application architectures, and networking. Experience with cloud platforms (AWS, Azure, GCP) and container orchestration (Kubernetes).
• Proficiency in Python, Bash, or similar scripting languages for automation and integration.
• Strong experience with LLMs (OpenAI, Anthropic, Gemini, Bedrock) and agentic AI solutions.
• Hands-on experience in designing AI architectures for enterprise IT environments.
• Proficiency in Python or similar languages for AI model integration and automation.

Role Summary

BrickRed Systems is seeking an experienced QA Engineer specializing in testing LLM agents and AI-driven workflows. This role focuses on evaluating agentic behavior, safety, reliability, grounding, automation quality, and deterministic vs. non-deterministic outcomes across advanced AI pipelines. You will collaborate closely with engineering, product, and AI research.

Key Responsibilities

• Design and execute comprehensive test strategies for LLM agents, agentic workflows, multi-step planners, and tool-using AI systems
• Implement Eval-Loops for continuous, automated evaluation of model performance, drift, consistency, and safety
• Build and maintain Golden Datasets to benchmark model accuracy, grounding, and regression behavior
• Use hill‐climbing evaluation techniques to iteratively improve prompts, policies, and model outputs
• Evaluate and test safety shield models (e.g., ShieldGemma) for content filtering, policy enforcement, and guardrail robustness
• Perform adversarial testing against hallucinations, ungrounded responses, safety violations, and reasoning failures
• Develop automation harnesses using Python, REST APIs, LangChain, PromptFlow, and LLM evaluation frameworks
• Assess agent behaviors across variations in prompts, contexts, tools, and reasoning paths
• Analyze responses for factuality, coherence, instruction-following, policy adherence, and chain-of-thought integrity (when applicable)
• Document findings, build structured bug taxonomies, and partner with engineering teams to resolve issues
• Drive improvements in reliability, latency, determinism, and consistent execution of multi-step agent behaviors

Required Technical Skills

• Strong QA experience (manual + automation) with AI/ML, LLMs, or agentic systems
• Hands-on experience with Python, automation frameworks, evaluation scripts, REST/JSON APIs
• Familiarity with LLM platforms (Azure OpenAI, OpenAI, Anthropic, Google Gemini, etc.)
• Experience with evaluation frameworks such as:
• PromptFlow evaluations
• DeepEval / Ragas / Trulens
• LangChain LCEL evaluations
• Custom scoring functions for grounding, correctness, toxicity, etc.
• Experience using or testing safety-shield models (e.g., ShieldGemma or similar)
• Understanding of techniques such as:
• Hill climbing optimization
• Agent loop testing
• Determinism scoring
• Self-reflection / self-correction evaluation
• Guardrail stress testing
• Scenario-based reasoning tests
• Strong analytical and problem‐solving skills for non-deterministic system behavior
• Excellent documentation, communication, and cross-team collaboration skills

About Brickred Systems:

Brickred Systems is a global leader in next-generation technology, consulting, and business process service companies. We enable clients to navigate their digital transformation. Brickred Systems delivers a range of consulting services to our clients across multiple industries around the world. Our practices employ highly skilled and experienced individuals with a client-centric passion for innovation and delivery excellence.

With ISO 27001 and ISO 9001 certification and over a decade of experience in managing the systems and workings of global enterprises, we harness the power of cognitive computing hyper-automation, robotics, cloud, analytics, and emerging technologies to help our clients adapt to the digital world and make them successful. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

Senior Developer, AI Evaluation & Cloud Infrastructure | Just Horizons Alliance

Join us to build the technical foundation for AI accountability.

The Role

Just Horizons Alliance is an 18-year-old applied research lab focused on ethics and technology. Our current focus is the AI Ethics Index, a measurement framework for evaluating AI systems on ethics, safety, and societal impact.

We need a senior engineer to own the technical infrastructure end-to-end: learn what exists, close critical gaps, and build something that lasts.

The evaluation methodology is validated and in use. We're now at the stage where the systems need to mature alongside the research. This is the first dedicated infrastructure hire for this work, and you'll shape how it scales.

What You'll Do

Months 1–3: Learn the System

Map the current architecture with Sophia Zitman (AIEI Team Lead). Understand the evaluation methodology, the data flows, and the infrastructure that supports them. Identify what needs to evolve for multi-domain benchmarking—reproducibility, security posture, test coverage, deployment pipeline. Begin implementing the highest-priority improvements.

Months 4–6: Build for Scale

Architect the infrastructure to support the next phase of the Index. CI/CD that maintains stability as the system grows. IAM and secret management built for a production environment. Experiment tracking that makes every evaluation run auditable. Documentation that enables the research team to work independently.

Months 7–12: Expand

Multi-domain benchmarking across education, healthcare, finance, and other sectors. Reproducibility standards that meet external scientific scrutiny. A system the research team can extend without engineering support for every change. At this point, the infrastructure should be stable enough that you're focused on capability, not maintenance.

Why This Role Is Difficult

This is infrastructure for a scientific standard, not a product feature.

Correctness and delivery both matter. A bug in the evaluation engine doesn't break a feature, instead it invalidates a measurement. A flawed pipeline doesn't slow things down, it compromises the credibility of the research. At the same time, methodology that never runs in production has no impact. The role requires both rigor and momentum.

You're translating between disciplines. Your stakeholders are researchers, ethicists, and governance specialists. You'll need to take concepts like \"operationalizing an ethical construct\" and turn them into data models and pipelines. This is a translation problem as much as an engineering problem.

The work is novel. There's no existing system to reference. The AI Ethics Index is defining what rigorous AI evaluation looks like. You'll be making architectural decisions in areas where best practices don't yet exist.

You'll have full ownership. This is not a role where you're executing someone else's technical vision. You're setting the direction. That means autonomy, but it also means accountability.

You're probably the right person if

You've built evaluation systems or data pipelines that other people depended on for correctness, not just uptime

You're comfortable with GCP and have deployed containerized workloads in a real production context

You've worked with LLM APIs and understand their reliability and reproducibility characteristics

You can read a paper about measurement methodology and turn it into a working data structure

You build for durability. Your code is still running 18 months later because you thought about the next person

You've worked somewhere between 5 and 50 people and you're comfortable being the person who figures things out without a playbook

You find working on AI ethics infrastructure more interesting than building another e-commerce checkout flow

You're probably not the right fit if

Enterprise environments make up most of your experience. This is not a large-team context

You need clearly defined requirements before you can start. The requirements here evolve through conversation with ethicists

You're based on the West Coast US or expect West Coast US working hours

You mainly build user-facing APIs and features — this is systems and infrastructure work

You're looking for a high-growth startup where shipping speed is everything. This is a scientific organization. Correctness is everything.

Hard Skills

These are the technical capabilities you need going in — or need to be able to build up fast using an AI coding agent. We're not looking for someone who ticks every box. We're looking for someone who closes gaps quickly and knows how to learn.

• Python — strong enough to design systems architecture and reason about failure modes, even if you work with AI assistance for implementation details
• Google Cloud Platform — specifically Cloud Run, IAM design, secret management, and containerized workload deployment in a real production context
• API and model documentation — able to read, write, and navigate API specs and model documentation fluently; you know how to figure out how a system behaves from its documentation without needing someone to walk you through it
• Structured step-by-step reasoning — when you hit a complex problem, you decompose it immediately and visibly into logical steps; you don't disappear into your head and come back with an answer, you think out loud and in sequence, which makes collaboration with the ethics and research team possible
• LLM API integration — understanding the reliability, reproducibility, and failure characteristics of external model endpoints
• Data pipeline architecture — building evaluation or measurement systems where correctness is non-negotiable, not just data-moving
• Experiment tracking and reproducibility standards — always looking to improve the evaluation pipeline; you understand what needs to be tracked, why reproducibility matters scientifically, and you find the right approach for the context without being dogmatic about tooling
• Statistical reliability concepts — enough to understand what inter-rater reliability means for evaluation output and why reproducibility matters scientifically

What you get

The role: You'll work directly with Sophia Zitman (AIEI Team Lead) as the technical backbone of the AI Ethics Index. Full engineering ownership of the evaluation engine.

The comp: Base salary $110,000.

The team: Small, split between ethicists and engineers. You will interview with Janet Kang (Executive Director) and Sophia Zitman (AIEI Team Lead).

The environment: Boston-based non-profit (501(c)(3)). East Coast US or Western Europe time zones. Collaborative but autonomous — Sophia won't micromanage, but she will hold you to a high standard of systems thinking.

The upside: You'll have built the technical foundation of what may become the globally referenced standard for AI system evaluation. That's a meaningful line on any CV — and a genuinely hard thing to have done.

A well-funded startup with strong enterprise traction is building a category-defining AI workbench to accelerate enterprise AI adoption.

The platform ingests messy, real workflows, automates them end-to-end, and continuously learns from human decision-making. This is a customer-focused, hands-on engineering role centred on shipping reliable, production-ready AI systems.

As a Customer facing Full stack Engineer, you'll partner with customers, product, and engineering to build and scale AI directly within enterprise workflows.

What You'll Do

• Build and deploy AI-powered features across frontend, backend, and platform

• Implement LLM systems including RAG, embeddings, agents, and document processing

• Rapidly prototype using real customer data and iterate quickly

• Ship user-facing AI with strong guardrails, reliability, and UX

• Optimize for performance, latency, safety, and scale

• Contribute to architecture, testing, and production readiness

• Develop reusable platform components and prompt frameworks

What You Bring

• BS required, Master's preferred

• Experience in a Forward Deployed Engineering role

• Proven track record deploying AI systems into production

• Strong hands-on experience with LLMs and RAG

• Solid software engineering fundamentals

• Comfort in 0 to 1, early-stage environments

• Familiarity with enterprise workflows and unstructured data

Compensation

• Up to $350,000 total comp

• Strong bonus

• Competitive equity

• Hybrid, 3 days onsite in Palo Alto

You'll help transform fragmented enterprise workflows into a continuously improving AI platform, shaping a product already seeing strong demand.

Director of AI

Location: Chicago, IL (Remote Eligible – must be US based)

Salary: $250,000 – 280,000 base + bonus

We’re partnering with a global education technology company undergoing a major transformation from a traditional publisher into a data and AI driven digital learning platform. The organization is investing heavily in AI and advanced data capabilities to deliver personalized learning experiences at global scale.

They are hiring a Director of AI to lead a team of AI researchers and data scientists responsible for developing and deploying advanced machine learning and Generative AI solutions across the enterprise.

The Role:

This is a highly strategic role that combines technical leadership, team management, and hands-on architectural oversight. The Director of AI will help define the long-term AI roadmap while working closely with product, engineering, and business stakeholders to bring production AI systems to life.

What you’ll do:

• Lead and grow a team of AI researchers and data scientists, providing technical mentorship and career development
• Define and execute the AI strategy and roadmap, with a strong focus on Generative AI capabilities
• Partner with product, engineering, and business teams to identify high-impact AI opportunities
• Oversee the design, development, and deployment of production-grade AI and ML systems
• Translate complex technical work into clear insights for both technical and executive stakeholders
• Manage project timelines, priorities, and team resources to ensure successful delivery of AI initiatives

What They’re Looking For

• PhD in Artificial Intelligence, Data Science, Computer Science, or a related technical field
• 8+ years of experience in AI, machine learning, or data science
• Proven experience leading teams of AI researchers or data scientists
• Deep expertise in machine learning, AI systems, and Generative AI technologies
• Strong communication skills with the ability to present technical concepts to senior leadership
• Experience collaborating cross-functionally with product, engineering, and business teams

Nice to Have

• Experience deploying Generative AI solutions in production environments
• Experience working in large-scale technology or digital product organizations
• Exposure to education technology or learning platforms

This role offers the opportunity to shape the AI strategy for a global platform impacting millions of learners worldwide, while leading a highly technical team working on cutting-edge machine learning systems.