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Senior Business Analyst Life & Annuities

Onsite in WDM office 4 days a week

Contract

Overview:

We are seeking an experienced Senior Business Systems Analyst (AI Enablement) to support ***’s AI transformation initiatives. This role will partner with ***’s BSA team, IT leadership, and PMO to understand current SDLC processes, identify pain points, gaps, and inconsistencies across teams, and translate findings into a more streamlined, AI-enabled operating model.

The BSA will assess our current requirements elicitation process and help define how an AI-infused approach can significantly improve the thoroughness, completeness, and quality of user requirements specifically for consumption by an AI coding agent. This includes identifying cross-system dependencies, non-functional requirements, and user personas from initial requirement elicitation through Jira story creation. This role will help transform our BSA capabilities by leveraging custom-built AI solutions to accelerate cycle time, improve consistency, and reduce downstream rework.

This role will also define measurable success criteria and develop metrics to evaluate process improvements and AI impact across the SDLC: gathering requirements across several other SDLC-related AI initiatives and provide light project management support across multiple AI workstreams.

Key Responsibilities

Assess current BA workflows, documentation standards, and impact analysis processes from user requirement elicitation through Jira story creation, identifying gaps, redundancies, inconsistencies and improvements across teams.

Identify friction points and define AI-enabled use cases with measurable business outcomes.

Drive feedback loops for AI proofs of concept (POCs) delivered to teams by gathering structured user input, measuring adoption and effectiveness, and incorporating insights into iterative improvements.

Develop clear, actionable requirements including user stories, acceptance criteria, non-functional requirements, personas, and upstream/downstream system impacts.

Determine and help establish processes or patterns to ensure user requirements align with current system capabilities. Proactively identify cross-system dependencies, technical constraints, gaps, and system limitations in collaboration with engineering teams to ensure requirements are technically feasible and implementation-ready.

Support backlog grooming, sprint planning, demos, and pilot validation sessions.

Track progress across multiple AI initiatives, manage dependencies and risks, and maintain clear stakeholder communication.

Develop and maintain lightweight project plans, timelines, and status reporting to ensure AI initiatives remain aligned with business priorities and strategic objectives.

Required Qualifications

5+ years of Business Analysis or Business Systems Analysis experience in technology or software environments.

Strong requirements elicitation, documentation, and facilitation skills.

Experience working in Agile environments with cross-functional teams.

Practical familiarity with AI tools (e.g., Claude Code CLI, ChatGPT, Copilot) and understanding of AI concepts (LLMs, prompt engineering, AI governance, and AI risk considerations).

Strong systems thinking, structured communication, and stakeholder management skills.

Preferred Experience

Experience implementing AI or automation solutions within enterprise environments.

Familiarity with AWS AI services (e.g., AWS Bedrock) or other enterprise AI platforms.

Familiarity with Jira, Confluence, GitHub, or similar SDLC ecosystems.

Experience supporting PMO processes or managing multiple concurrent initiatives along with a functional understanding of Agile practices.

Financial services or insurance industry experience.

Success Measures

Successful delivery of an AI-enabled solution for ***’s BSA team.

Improved BA workflow efficiency, quality, and consistency.

High-quality, implementation-ready requirements that reduce downstream rework and delivery thrash.

Effective coordination, transparency, and measurable progress across AI initiatives.

Granite delivers advanced communications and technology solutions to businesses and government agencies throughout the United States and Canada. We provide exceptional customized service with an emphasis on reliability and outstanding customer support and our customers include over 85 of the Fortune 100. Granite has over $1.85 Billion in revenue with more than 2,100 employees and is headquartered in Quincy, MA. Our mission is to be the leading telecommunications company wherever we offer services as well as provide an environment where the value of each individual is recognized and where each person has the opportunity to further their growth and achieve success.

Granite has been recognized by the Boston Business Journal as one of the "Healthiest Companies" in Massachusetts for the past 15 consecutive years.

Our offices have onsite fully equipped state of the art gyms for employees at zero cost.

Granite's philanthropy is unparalleled with over $300 million in donations to organizations such as Dana Farber Cancer Institute, The ALS Foundation and the Alzheimer's Association to name a few.

We have been consistently rated a "Fastest Growing Company" by Inc. Magazine.

Granite was named to Forbes List of America's Best Employers 2022, 2023 and 2024.

Granite was recently named One of Forbes Best Employers for Diversity.

Our company's insurance package includes health, dental, vision, life, disability coverage, 401K retirement with company match, childcare benefits, tuition assistance, and more.

If you are a highly motivated individual who wants to grow your career with a fast paced and progressive company, Granite has countless opportunities for you.

EOE/M/F/Vets/Disabled

Job Description

We are seeking a highly skilled and experienced Lead AI Engineer to join our dynamic team. The ideal candidate will excel at identifying and articulating complex business problems, and will develop innovative, scalable, and robust AI/ML solutions to address these challenges. Responsibilities will include designing, building, and deploying enterprise-grade AI systems, specifically focused on:

• 
  
• Agentic AI solutions to automate operational processes (e.g., interpreting trouble tickets, performing basic troubleshooting, interacting with online portals, data entry).
  
• Retrieval-Augmented Generation (RAG) and ColBERTv2 pipelines for parsing, indexing, and querying enterprise documents to facilitate answers related to process guidelines, product knowledge, and training materials.
  
• Function calling solutions leveraging Large Language Models (LLMs) to automate and perform precise actions in enterprise workflows.
  
• Developing and applying reinforcement learning strategies to optimize and automate decision-making processes within enterprise operations.
  

This role requires hands-on expertise with model fine-tuning, training pipelines, post-training optimization techniques (e.g., model distillation), classification models, and integrating AI systems within complex enterprise environments.

Duties and Responsibilities

• 
  
• Develop and implement AI solutions leveraging fine-tuned Large Language Models (e.g., OpenAI models, LLaMA, Mistral).
  
• Design, develop, and optimize Retrieval-Augmented Generation (RAG) pipelines using advanced vector databases (e.g., FAISS, Pinecone, Milvus).
  
• Build and enhance agentic AI systems utilizing frameworks like LangChain, AutoGPT, or similar automation frameworks.
  
• Deploy scalable ColBERTv2 architectures for semantic retrieval and classification.
  
• Create robust pre-processing and post-processing pipelines to enhance model performance, accuracy, and interpretability.
  
• Collaborate closely with cross-functional teams, including product managers, business stakeholders, data scientists, and software engineers.
  
• Implement best practices in model distillation, quantization, and optimization for deployment in production environments.
  
• Ensure compliance with enterprise-grade security, privacy standards, and data governance practices.
  
• Provide leadership and mentorship to team members, supporting their technical development and career growth through coaching, training, and performance feedback.
  
• Drive timely and successful completion of AI/ML projects by setting clear milestones, tracking progress, removing blockers, and aligning resources
  

Required Qualifications

• 
  
• Bachelor's degree in Computer Science, Data Science, Machine Learning, AI, or related fields; advanced degree strongly preferred.
  
• 5+ years of proven experience developing and deploying production-grade AI/ML systems.
  
• Strong programming skills in Python, familiarity with libraries/frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain.
  
• Demonstrated expertise with LLM fine-tuning (e.g., LoRA, PEFT), distillation, and model optimization.
  
• Practical experience implementing RAG pipelines with embedding technologies and vector stores (e.g., FAISS, Pinecone).
  
• Proven track record building agentic AI systems capable of interacting with multiple enterprise applications and platforms.
  
• Solid understanding of NLP techniques, Transformer architectures, semantic search, and document retrieval technologies (e.g., ColBERT).
  
• Hands-on experience with reinforcement learning techniques, including designing, training, and deploying reinforcement learning models.
  

Preferred Qualifications:

• 
  
• Master's or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, or related field.
  
• Familiarity with cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI).
  
• Experience with containerization (Docker, Kubernetes) and deployment pipelines (CI/CD).
  
• Knowledge of advanced AI frameworks and model inference engines such as Triton Inference Server, TensorRT, and ONNX.
  
• Familiarity with model monitoring, observability tools, and techniques to ensure long-term reliability and performance.
  
• Strong communication and interpersonal skills with the ability to clearly articulate complex technical solutions to non-technical stakeholders.
  
• Experience in regulated industries or environments requiring strict compliance and data governance standards.
  

At Rite-Hite, your work makes an impact. As the global leader in loading dock and door equipment, we design and deliver solutions that keep our customers safe, secure, and productive. Here, you'll find innovation, stability, and the chance to grow your career as part of a team that's always looking ahead.

ESSENTIAL DUTIES AND RESPONSIBILITIES

To perform this job successfully, an individual must be able to perform each essential duty satisfactorily.

• Design and build AI-powered applications using Large Language Models (LLMs) for enterprise use cases.
• Develop Retrieval-Augmented Generation (RAG) solutions using structured and unstructured enterprise data such as documents, manuals, tickets, ERP data, and knowledge bases.
• Build and orchestrate AI agents that can reason, plan, and interact with tools, APIs, and workflows.
• Implement guardrails for AI systems including prompt safety, data protection, hallucination mitigation, access control, and output validation.
• Work with multimodal AI models including text, image, and video use cases such as video analysis, summarization, and optimization.
• Integrate AI solutions with existing enterprise systems such as Salesforce, ERP platforms, data lakes, APIs, and internal applications.
• Partner with security and compliance teams to ensure responsible AI usage, data privacy, and governance.
• Prototype quickly, then harden solutions for production with monitoring, logging, evaluation, and performance optimization.
• Mentor and upskill existing developers on AI concepts, patterns, and best practices.

Required Skills & Experience

• 5+ year of full stack development experience.
• Strong software engineering background with experience building production-grade applications.
• Hands-on experience with modern LLM platforms such as OpenAI, Azure OpenAI, Anthropic, or similar.
• Practical experience building RAG pipelines using vector databases and embedding models.
• Experience with prompt engineering, prompt versioning, and evaluation techniques.
• Solid Python experience for AI development.
• Experience integrating AI services with REST APIs, microservices, and cloud-native architectures.
• Familiarity with cloud platforms such as AWS or Azure, including deployment, scaling, and security concepts.
• Understanding of data formats such as JSON, XML, and document-based data.
• Ability to translate business problems into AI-driven technical solutions.

Preferred Qualifications

• Experience with vector databases such as Pinecone, FAISS, Weaviate, or similar.
• Familiarity with frameworks such as LangChain, LlamaIndex, Semantic Kernel, or equivalent orchestration tools.
• Experience implementing AI safety controls, policy enforcement, and evaluation frameworks.
• Exposure to video or image models and multimodal AI use cases.
• Experience working in enterprise environments with security, compliance, and change management considerations.
• Prior experience mentoring or leading developers in new technical domains.

What We Offer

At Rite-Hite, we take care of our people - because when you're supported, you can do your best work. Our benefits are designed to support your health, your future and your life outside of work:

• Health & Well-being: Comprehensive medical, dental, and vision coverage, plus life and disability insurance. A robust well-being program with an opportunity to receive an extra day off and more.

• Financial Security: A strong retirement savings program with 401(k), company match, and profit sharing.

• Time for You: Paid holidays, vacation time, and personal/sick days each year.

Join us and build a career where you're supported - at work and beyond.

Rite-Hite is proud to be an Equal Opportunity Employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic under federal, state, or local law.In accordance with VEVRAA, we are committed to providing equal employment opportunities for protected veterans.We are also committed to maintaining a drug-free workplace for the safety of our employees and customers.

• 
  
• A typical day will involve a mix of hands-on coding, architectural design, and research.
  
• The engineer will spend a significant portion of their time in Python, building and optimizing agentic AI systems using frameworks like LangChain.
  
• This includes integrating these agents with our backend services and deploying them using CI/CD pipelines into our cloud environment.
  
• They will also be responsible for researching and testing new agentic models and frameworks, monitoring agent behavior in production, and collaborating with data scientists and business stakeholders to refine requirements and ensure the ethical deployment of AI solutions.
  

• 
  
• Python
  
• JavaScript/TypeScript
  
• AI Tools and Libraries (e.g. LangGraph, LangChain, Deep Agents, Claude Skills, etc.)
  
• AI Models (e.g. Claude, OpenAI, etc.)
  
• AI Concepts (e.g. Prompt Engineering, RAG, Agentic AI, etc.)
  
• Distributed SDLC/DevOps (e.g. github, pipelines, VS Code, testing frameworks, etc.)
  
• Platforms (Container Platforms, Cloud Platforms, Document Databases, AWS)
  
• API Design
  

• 
  
• Deep hands-on experience in Python for AI/ML development.
  

• 
  
• Generative AI Development: Proven experience developing Gen AI or AI/ML solutions, from use case conceptualization to production deployment.
  
• Infrastructure & DevOps: Strong understanding of cloud environments (AWS preferred), LLM hosting, CI/CD pipelines, Docker, and Kubernetes.
  
• Agentic AI Concepts: Knowledge of agentic/autonomous systems (e.g., reasoning, planning, tool use).
  

• 
  
• Proficiency in Python development and FastAPI/Flask frameworks, along with SQL.
  
• Familiarity with agentic AI frameworks and concepts such as LangChain, LangGraph, AutoGen, Model Context Protocol (MCP), Chain of Thought prompting, knowledge stores, and embeddings.
  
• Experience developing autonomous agents using cloud-based AI services.
  
• Experience with prompt engineering techniques and model fine-tuning.
  
• Strong understanding of reinforcement learning, planning algorithms, and multi-agent systems.
  
• Experience working across cloud platforms (AWS, Azure, GCP) and deploying AI solutions at scale.
  

Role: Product Manager - Sales and Support Tech with Generative AI / Agentic AI

Duration: 12 months

Location: San Jose, CA (Hybrid)

Job Description

We are seeking a dynamic and experienced Product Manager to join our team, focusing on the Sales and Support technology domain. The ideal candidate will have a strong background in product management, with a specific emphasis and track record on leveraging Generative AI to enhance customer experience and drive business growth.

Key Responsibilities:

• Product Strategy and Vision: Develop, articulate, and champion a clear product vision and strategy for Sales and Support technologies, incorporating Generative AI capabilities to innovate and improve customer interactions.

• Market Research and Analysis: Conduct thorough market research to identify customer needs, market trends, and competitive landscape. Use these insights to inform product development and positioning.

• Roadmap Development: Create and maintain a detailed 4-quarterly product roadmap th aligns with business objectives and customer needs. Prioritize features and enhancements based on impact and feasibility. Present roadmap progress and insights to senior leadership and cross-functional stakeholders.

• Cross-functional Collaboration: Partner closely with engineering, UX design, sales, legal, and support teams to ensure successful product development and launch. Facilitate communication, alignment and collaboration across distributed teams and geographies.

• Customer Engagement: Engage with customers & key stakeholders to gather feedback, understand pain points, and validate product concepts. Use this feedback to drive continuous improvement and innovation.

• Performance Metrics: Define and track key performance indicators (KPIs) to measure product success and identify areas for improvement. Use data-driven insights to make informed decisions.

• Generative AI / Agentic AI Integration: Leverage Generative AI / Agentic AI technologies to develop innovative solutions that enhance sales and support processes. Stay updated on the latest advancements in AI and apply them to product development. Collaborate with business, engineering and data science teams to prototype, validate, and launch AI-powered features that drive automation, personalization, and efficiency

Qualifications:

• Education: Bachelor's degree in Computer Science, Engineering, Business, or a related field. MBA or advanced degree is a plus.

• Experience: Minimum of 7 years of product management experience, with a focus on Sales and Support technologies. Proven track record of successfully launching and managing products.

• Technical Skills: Strong understanding and track record of implementing Generative AI / Agentic AI technologies and their applications in the Sales and Support domain. Experience with AI/ML frameworks and tools is highly desirable.

• Experience with Leading AI Platforms: Experience with industry-leading AI ecosystems such as Microsoft Azure OpenAI Service, Amazon Bedrock, or AWS SageMaker is highly desirable. Familiarity with integrating these platforms into enterprise-scale CRM and support systems is a strong advantage. Demonstrated success in leveraging these technologies to design scalable, intelligent solutions that enhance user productivity, automate workflows, and drive measurable business outcomes will set you apart.

• Analytical Skills: Excellent analytical and problem-solving skills. Ability to interpret complex data and make data-driven decisions.

• Communication Skills: Strong verbal and written communication skills. Ability to effectively communicate with technical and non-technical stakeholders.

• Leadership: Demonstrated leadership skills with the ability to influence and inspire crossfunctional teams. Strong project management skills and attention to detail.

Why Join Us:

• Innovative Environment: Be part of a forward-thinking company that values innovation and creativity. Work on cutting-edge technologies and make a significant impact on the industry.

• Collaborative Culture: Join a collaborative and inclusive team that values diverse perspectives and fosters a culture of continuous learning and growth.

Job Title: Sr AI Platform Engineer- AI Platform Engineer (Guardrails, Observability & Evaluation Infrastructure)

Location, Charlotte, NC, USA (3 days onsite)

Role Overview

AI Platform Engineer to design and build the foundational components that power enterprise scale GenAI applications. This includes data guardrails, model safety tooling, observability pipelines, evaluation harnesses, and standardized logging/monitoring frameworks. This role is critical for enabling safe, reliable, and compliant AI development across multiple use cases, teams, and business units. Idea is to create the common platform services that AI team will build upon.

Key Responsibilities

1. Guardrails, Safety & Governance

• Design and implement data guardrail frameworks (pre processing, redaction, PII/PHI filtering, DLP integration, prompt defenses).

• Build "Model Armor" components such as:

o Input validation & sanitization

o Prompt injection defenses

o Harmful content detection & policy enforcement

o Output filtering, fact checking, grounding checks

• Integrate safety tooling (policy engines, classifiers, DLP APIs, safety models).

• Collaborate with Security, Compliance, and Data Privacy teams to ensure frameworks meet enterprise governance requirements.

2. Observability Frameworks

• Build and maintain observability pipelines using tools like Arize AI (tracing, quality metrics, dataset drift/hallucination tracking, embedding monitoring).

• Define and enforce platform wide standards for:

o Tracing LLM calls

o Token usage and cost monitoring

o Latency and reliability metrics

o Prompt/model version tracking

• Provide reusable SDKs or middleware for engineering teams to adopt observability with minimal friction.

3. Logging, Monitoring & Telemetry

• Design standardized LLM-specific logging schemas, including:

o Inputs/outputs

o Model metadata

o Retrieval metadata

o Safety flags

o User context and attribution

• Build monitoring dashboards for performance, cost, anomalies, errors, and safety events.

• Implement alerting and SLOs/SLIs for LLM inference systems.

4. Evaluation Infrastructure

• Architect and maintain evaluation harnesses for GenAI systems, including:

o RAG evaluation (faithfulness, relevance, hallucination risk)

o Summarization/QA evaluation

o Human-in-the-loop review workflows

o Automated eval pipelines integrated into CI/CD

• Support frameworks such as RAGAS, G Eval, rubric scoring, pairwise comparisons, and test case generation.

• Build reusable tooling for teams to write, run, and track model evaluations.

5. Platform Engineering & Reusable Components

• Develop shared libraries, APIs, and services for:

o Prompt management/versioning

o Embedding pipelines and model wrappers

o Retrieval adapters

o Common data loaders and document preprocessing

o Tool/function schemas

• Drive consistency across teams with standards, reference architectures, and best practices.

• Review system designs across use cases to ensure alignment to platform patterns.

6. Collaboration & Enablement

• Partner with AI engineers, product teams, and data scientists to understand cross cutting needs and convert them into reusable platform features.

• Create documentation, onboarding guides, examples, and developer tooling.

• Provide internal training (brown bags, workshops) on guardrails, observability, and evaluation frameworks.

Required Qualifications

Technical Skills

• 5–10+ years software engineering or ML infrastructure experience.

• Strong Python engineering fundamentals (FastAPI, async, typing/Pydantic, testing).

• Experience with model safety/guardrails approaches (prompt injection defense, PII redaction, toxicity filters, policy enforcement).

• Hands on with Arize AI, LangSmith, or similar LLM observability platforms.

• Experience creating evaluation frameworks using RAGAS, G Eval, or custom rubric systems.

• Strong familiarity with vector databases (Pinecone, Weaviate, Milvus), embeddings, and retrieval pipelines.

• Solid understanding of LLM architectures, tokenization, embeddings, context limits, and RAG patterns.

• Experience in cloud (GCP preferred), Kubernetes/GKE, containers, and CI/CD.

• Strong understanding of security, governance, DLP, data privacy, RBAC, and enterprise compliance requirements.

Soft Skills

• Strong documentation and communication skills.

• Ability to influence engineering teams and standardize best practices.

• Comfortable working across multiple stakeholders—platform, security, ML engineering, product.

Nice to Have

• Experience with LangChain/LangGraph or LlamaIndex orchestrations.

• Experience with , Rebuff, Protect AI, or similar LLM security tooling.

• Experience with GCP Vertex AI pipelines, Model Monitoring, and Vector Search.

• Familiarity with knowledge graphs, grounding models, fact checking models.

• Building SDKs or developer frameworks adopted across multiple teams.

• On prem or hybrid AI deployment experience.

Overview

Architects and builds the infrastructure and tooling that powers AI agent development across the Software Development Lifecycle (SDLC). Develops production-grade agentic systems, orchestration frameworks, and observability solutions that enable teams to build, deploy, and monitor reliable AI agents at scale. Plays a key role in defining and implementing the next generation of SDLC through AI-first innovation and comprehensive instrumentation.

What We're Looking For

You demonstrate sharp product sense for high-impact automation opportunities, technical taste in implementation decisions, and the ability to clearly articulate trade-offs. You know when to apply AI agent solutions versus simpler approaches and can explain the \"why\" behind architectural choices.

You excel at 0-to-1 (and 1-to-100) product development, comfortable operating in ambiguous environments where requirements emerge through experimentation and iteration rather than upfront specification.

Key Responsibilities

AI Agent Development & Automation:

• Develop production-grade AI agents that eliminate manual handoffs across the SDLC

• Create custom integrations and CLI tools that give agents deep understanding of internal systems and codebases

• Design comprehensive testing strategies to ensure agent reliability and output quality

• Implement \"Golden Path\" scaffolding that embeds organizational standards into new projects

• Build AI solutions that improve codebase navigation, documentation, and developer workflows

• Identify workflow bottlenecks and deliver measurable impact through intelligent automation

• Shape SDLC evolution by identifying AI-first opportunities and proving outcomes through experimentation

Agent Infrastructure & Platform:

• Architect and maintain production infrastructure supporting agent deployment, lifecycle management, and scaling

• Develop agent frameworks, templates, and SDKs that accelerate agent development

• Create governed Model Context Protocol (MCP) catalog enabling compliant agent-to-agent and agent-to-MCP communication

• Implement governance controls for agent behavior, permissions, and system access

Observability & Performance Analytics:

• Design and implement metrics, monitoring, and logging infrastructure for AI agents and development workflows

• Build dashboards that provide actionable insights into developer productivity, tool adoption, and agent performance

• Establish KPIs and measurement frameworks to quantify the impact of AI-powered automation

• Create alerting and anomaly detection systems to ensure reliability of agents and tooling

• Analyze telemetry data to identify optimization opportunities and guide strategic investment decisions

Collaboration & Impact:

• Partner across teams to drive adoption of AI-powered tooling and process transformation

• Stay current with LLM technologies and coach colleagues on AI-assisted development and automation best practices

• Rapidly prototype solutions to validate use cases and prove value quickly

• Communicate data-driven insights to stakeholders through clear visualizations and reports

Preferred Qualifications:

• 5-7+ years of software engineering experience building production systems

• Proven experience building agentic systems using LLM orchestration frameworks

• Hands-on expertise with AI-powered development tools (code assistants, AI-enhanced editors)

• Strong foundation in SDLC, system design, and internal tooling development

• Experience with observability tools and practices including metrics collection, logging frameworks, and dashboard development

• Full-stack technical proficiency:

• Languages: Java, Python, JavaScript/TypeScript

• Frameworks: Angular, Spring Boot

• CI/CD platforms and cloud infrastructure (AWS)

• Monitoring/observability tools (e.g., Prometheus, Grafana, CloudWatch)

• Passion for transforming software development through AI innovation and data-driven decision making

# LI-CGTS

# TS-2505

AI Ethics Specialist, Standards, Measurement & Governance | Just Horizons Alliance

Join us to define the standards that hold AI systems accountable.

The situation

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 currently have a first version of the framework that is validated and in use. Now we're investing in the next phase: sharper indicator definitions, stronger construct validity, governance processes that hold up to external scrutiny, and measurements that work across domains from education to healthcare to finance.

This is the first dedicated hire to drive the standards and governance layer end-to-end.

What you'll actually do

Months 1–3: Learn the system

Work through the existing L4 indicator library with Sophia. Understand where definitions need tightening, which constructs require the most interpretation, and how the evaluation engine turns indicators into measurements. Start giving developers working definitions they can implement.

Months 4–6: Build the governance infrastructure

Lead the development of a versioning and change control process for the Index. Define disclosure policies. Formalize internal ethical oversight processes. Collaborate with domain experts in education, healthcare, and finance to validate indicators across contexts.

Months 7–12: Drive the standard

Be the person who gives definitive answers on construct interpretation. Manage the L4 indicator framework as a living, governed document. Represent the methodological rigor of the Index in external conversations with regulators, academics, and the organizations being evaluated.

Why this role is hard

You're working at the frontier of a field that does not have settled answers. There is no ISO standard for AI ethics measurement. The frameworks you're building will be contested by academics, challenged by the AI companies being evaluated, and scrutinized by regulators. You need to make defensible decisions under genuine uncertainty, document your reasoning clearly, and communicate it to people who will disagree.

The daily work involves uncomfortable specifics. What does \"sexually explicit content\" mean when an LLM is used in a youth education context—a tutoring app, a storytelling tool, an educational assistant? Where exactly is the boundary? You have to define it in terms a developer can implement and an auditor can verify.

The pace is weeks, not semesters.

You're probably the right person if

You've taken an abstract ethical principle and turned it into something a developer could build or a compliance team could audit

You understand NIST AI RMF or the EU AI Act at a working level — not awareness, but enough to argue about the details

You have external credibility in the field: publications, recognised work, advisory roles, or a title that carries weight

KYC, compliance, or governance experience is part of your background alongside ethics expertise

You work at the pace of decisions, not the pace of studies

You can hold a substantive conversation with a software developer about API behaviour and with a philosopher about construct validity — on the same day

You can read an inter-rater reliability methodology and understand what it means for your indicator definitions

You're probably not the right fit if

Your background is purely academic ethics — you've written and published but never operationalized anything

You need months of research before committing to a position on a specific indicator definition

You're primarily a communicator or writer about AI ethics rather than a practitioner of governance

You're based on the West Coast US or don't work in East Coast US or Western Europe time zones

You see \"working with developers\" as someone else's job

Hard Skills

These are the domain and technical capabilities you need going in — or need to be able to build up fast. You don't need to be an engineer. But you do need to learn quickly, including using AI tools to close knowledge gaps on the fly.

• NIST AI RMF and EU AI Act — working-level knowledge, not awareness. Enough to argue about the details and identify where a specific AI system fails to comply
• Construct operationalization — demonstrated experience translating an abstract ethical principle into a bounded, testable indicator that someone else can use
• Governance documentation — writing versioning policies, change control frameworks, and disclosure protocols that other people actually use day to day
• AI evaluation methodology — familiarity with how AI systems are benchmarked, where measurement goes wrong, and what validity means in a scientific context
• Basic technical literacy — able to read API documentation, understand what a model endpoint does.
• Statistical reliability concepts — inter-rater reliability, aggregation methods, and what it means for a measurement to be valid versus merely reliable
• KYC or compliance frameworks — experience building governance processes that have real enforcement teeth, not just principles documents that no one is held to

What you get

The role: Work directly with Sophia Zitman (AIEI Team Lead) as the person who owns the methodological integrity of the AI Ethics Index. Direct daily collaboration with the development team.

The comp: $110,000

The team: Small, split between ethicists and engineers. Interview panel: Janet Kang and Sophia Zitman.

The environment: Boston-based non-profit (501(c)(3)). East Coast US or Western Europe time zones strongly preferred. Deliberate, rigorous culture.

The upside: You'll have built the governance foundation of what may become the globally referenced standard for AI ethics measurement. That is a genuinely consequential body of work.

Duration: 12 months (possible extension)

Description:

Job Title: Senior AI Fullstack Engineer

The Position

• We advance science so that we all have more time with the people we love. Client's Early Clinical Development (ECD) department is seeking a talented and motivated Software Developer reporting to the Director of software engineering at The Clinical Data Insights & Automation team (CDI&A).
• The CDI&A team collaborates with a broad range of stakeholders involved in the clinical development process (e.g., Clinical Science, Clinical Operations, Medical Writing, Quality, Regulatory). It develops industry-leading solutions for highly complex business problems. To manage the design and pilot of these software products, they apply a high degree of ingenuity and creativity while maintaining a finger on the pulses of the rapidly changing tech and healthcare landscapes.
• The Software Engineer will primarily be responsible for designing, developing, and deploying software which interacts with cutting-edge generative AI models and applications in collaboration with AI scientists, full stack developers, and others. Their work will directly impact our ability to create and deliver innovative solutions that leverage AI to solve complex problems and enhance user experiences.

The Opportunity:

• Innovate and develop software applications to support clinical development
• Identify and integrate AI/LLM capabilities to enhance data processing and natural workflows.
• Design intuitive, user-centric interfaces.
• Code Quality and Documentation: Write clean, maintainable, and well-documented code. Participate in code reviews and contribute to best practices in software development.
• Research and Innovation: Stay up-to-date with the latest advancements in generative AI and machine learning. Evaluate new technologies and methodologies to continuously improve our solutions.
• Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, and product managers to integrate generative AI capabilities into our products and services.
• Deployment and Monitoring: Develop and maintain robust deployment pipelines for AI-enhanced applications. Monitor pipeline performance in production and implement necessary improvements.

Who You Are:

• An experienced full stack developer capable of bringing your expertise to our existing and upcoming AI applications/projects as both a leader and individual contributor.
• Someone with a clear understanding of the current landscape of AI & AI-based applications, including potential benefits, limitations, and standard of practice.

Minimum Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of full stack development experience
• Strong proficiency in either a front-end framework (Vue.js, React, or similar) and a backend web frameworks in Python and/or JavaScript (Django, FastAPI, Flask, Next.js, or similar)
• 4+ years experience with front-end frameworks (preferably Vue.js)
• 2+ years of developing and deploying AI/ML solutions or applications
• Experience designing and developing RESTful APIs (with e.g. Python FastAPI).
• Familiarity with prompt engineering
• Proficiency with containerized workflows and architectures (Podman, Docker, Kubernetes)
• Strong automated software testing skills (Python unittest, jest, Playwright)
• Familiar with Agile methodologies
• Excellent analytical and problem-solving skills with a track record of tackling complex technical challenges.
• Leading system design and implementing scalable, fault-tolerant solutions for complex, distributed computing challenges.
• Strong interpersonal and communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Experience with cloud platforms (e.g. AWS) and modern data platforms (e.g., Snowflake).
• Experience implementing chatbots, retrieval-augmented generation (RAG) systems, and integrating LLMs into applications (AI-assisted automation)

Preferred Qualifications:

• Experience building AI agents, fine-tuning LLM models, and evaluating bias and fairness with LLM systems
• Experience in developing Microsoft Word add-ins using Office.js.
• Experience with web technologies like JWT, WebSockets, etc.
• Experience with Huggingface, Langchain, TensorFlow, PyTorch, or similar.
• Familiarity with DevOps, infrastructure, and continuous integration concepts.
• Familiarity with CRDT technologies like Yjs.
• Experience with using NLP/LLMs on clinical text.
• Basic knowledge of clinical drug development

About US Tech Solutions:

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Recruiter Details:

Name: Prateek Chaturvedi

Email:

Internal Id: 26-06298

This is a multi-year contract with our direct client.

No third parties!

The Early Clinical Development (ECD) department with our South San Francisco, CA client is seeking a talented and motivated Senior AI Full Stack Engineer reporting to the Director of software engineering at The Clinical Data Insights & Automation team (CDI&A). The CDI&A team collaborates with a broad range of stakeholders involved in the clinical development process (e.g., Clinical Science, Clinical Operations, Medical Writing, Quality, Regulatory). It develops industry-leading solutions for highly complex business problems. To manage the design and pilot of these software products, they apply a high degree of ingenuity and creativity while maintaining a finger on the pulses of the rapidly changing tech and healthcare landscapes.

The Software Engineer will primarily be responsible for designing, developing, and deploying software which interacts with cutting-edge generative AI models and applications in collaboration with AI scientists, full stack developers, and others. Their work will directly impact our ability to create and deliver innovative solutions that leverage AI to solve complex problems and enhance user experiences.

The Opportunity:

• Innovate and develop software applications to support clinical development
• Identify and integrate AI/LLM capabilities to enhance data processing and natural workflows.
• Design intuitive, user-centric interfaces.
• Code Quality and Documentation: Write clean, maintainable, and well-documented code. Participate in code reviews and contribute to best practices in software development.
• Research and Innovation: Stay up-to-date with the latest advancements in generative AI and machine learning. Evaluate new technologies and methodologies to continuously improve our solutions.
• Collaborate with Cross-Functional Teams: Work closely with data scientists, engineers, and product managers to integrate generative AI capabilities into our products and services.
• Deployment and Monitoring: Develop and maintain robust deployment pipelines for AI-enhanced applications. Monitor pipeline performance in production and implement necessary improvements.

Who You Are:

• An experienced full stack developer capable of bringing your expertise to our existing and upcoming AI applications/projects as both a leader and individual contributor.
• Someone with a clear understanding of the current landscape of AI & AI-based applications, including potential benefits, limitations, and standard of practice.

Minimum Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
• 5+ years of full stack development experience
• Strong proficiency in either a front-end framework (js, React, or similar) and a backend web frameworks in Python and/or JavaScript (Django, FastAPI, Flask, Next.js, or similar)
• 4+ years experience with front-end frameworks (preferably js)
• 2+ years of developing and deploying AI/ML solutions or applications
• Experience designing and developing RESTful APIs (with e.g. Python FastAPI).
• Familiarity with prompt engineering
• Proficiency with containerized workflows and architectures (Podman, Docker, Kubernetes)
• Strong automated software testing skills (Python unittest, jest, Playwright)
• Familiar with Agile methodologies
• Excellent analytical and problem-solving skills with a track record of tackling complex technical challenges.
• Leading system design and implementing scalable, fault-tolerant solutions for complex, distributed computing challenges.
• Strong interpersonal and communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.
• Experience with cloud platforms (e.g. AWS) and modern data platforms (e.g., Snowflake).
• Experience implementing chatbots, retrieval-augmented generation (RAG) systems, and integrating LLMs into applications (AI-assisted automation)

Preferred Qualifications:

• Experience building AI agents, fine-tuning LLM models, and evaluating bias and fairness with LLM systems
• Experience in developing Microsoft Word add-ins using js.
• Experience with web technologies like JWT, WebSockets, etc.
• Experience with Huggingface, Langchain, TensorFlow, PyTorch, or similar.
• Familiarity with DevOps, infrastructure, and continuous integration concepts.
• Familiarity with CRDT technologies like Yjs.
• Experience with using NLP/LLMs on clinical text.
• Basic knowledge of clinical drug development