Top AI Ethics Jobs in Boston, MA

Evaluate and improve AI-generated outputs for accuracy, clarity, quality, and business alignment. Develop and refine prompts, annotate data, conduct rubric-based assessments, fact-check content, and provide actionable feedback on model performance. Create and edit technical documentation, strategy reports, market analyses, business cases, executive summaries, and professional communications. The role requires strong analytical reasoning, writing, research, quality assurance, and attention to detail.

Develops and maintains AI governance policies, frameworks, and controls aligned with regulatory and industry standards. Conducts AI model risk assessments covering bias, explainability, data quality, and security; evaluates organizational and vendor risks; supports audits; designs controls; and partners with Legal, Privacy, Security, and Technology teams. The role also promotes compliant AI practices and organizational awareness while applying advanced AI/ML knowledge.

Lead AiLO portfolio integrating AI into K-12 systems: set strategy, design and draft high-stakes deliverables, manage complex projects, mentor teams, cultivate partnerships, and represent ILO externally to scale responsible AI adoption in education.

Serve as the senior AI advisor to the VHA National Artificial Intelligence Institute. Develop AI risk-management playbooks, governance guidance, risk stratification methods, enterprise AI strategies, training, and oversight materials. Advise AI use-case owners and government stakeholders, translate federal AI policy into actionable guidance, support health information and ModelOps initiatives, and research emerging AI governance practices. The role is remote, advisory, full-time, and contingent.

Owns Navitus’s enterprise AI governance and enablement program, including governance frameworks, risk assessments, compliance monitoring, use-case inventory, vendor AI evaluations, reporting, and committee operations. Partners with Legal, Compliance, Privacy, Security, IT, Engineering, and Learning Services to support responsible AI adoption. Leads proof-of-concept initiatives, develops policies and training strategies, tracks regulatory developments, mentors others, and presents governance insights and recommendations to leadership.

Evaluates AI-generated responses for accuracy, completeness, safety, and policy alignment during client implementations. Translates client use cases and risk tolerances into rubrics, prompts, test coverage, prompt banks, and golden sets. Reviews outputs, identifies hallucinations and other risks, tracks regression and drift, documents findings, and produces quality reports. Partners with clients, product, and engineering teams to validate fixes and support reliable release and governance decisions.

Supports responsible AI governance by developing frameworks, conducting fairness and risk assessments, monitoring regulatory requirements, maintaining compliance documentation, educating stakeholders, and improving AI oversight practices. Works across technical, legal, compliance, risk, and business teams to promote ethical, transparent, accountable, and trustworthy AI systems.

Evaluates and compares AI-generated responses in English and Italian for accuracy, relevance, reasoning, clarity, safety, cultural appropriateness, and overall usefulness. Applies detailed annotation guidelines consistently across varied tasks, documents evidence-based decisions, meets productivity expectations, participates in training and calibration, and adapts to quality feedback. Requires strong Italian and English fluency, analytical judgment, attention to detail, and comfort with repetitive, high-volume evaluation work.

Works with enterprise clients to drive AI adoption by assessing readiness, identifying use cases, building adoption roadmaps, delivering training, and managing communications and champion programs. Develops prompt guides, AI-enabled workflows, dashboards, and adoption metrics. Facilitates workshops and office hours, supports responsible AI and safety practices, maintains risk registers, and creates reusable resources to scale and sustain AI usage.

Evaluate AI models for dangerous CBRNE-related outputs, designing adversarial prompts, multi-turn attack chains, and threat models. Assess technical accuracy and real-world risk, distinguish open-source information from harmful uplift, score responses using severity rubrics, and document failures. Collaborate with AI researchers and policy teams to improve model safeguards and evaluation frameworks while following strict ethical and operational security protocols.