Senior AI Governance Analyst at Steampunk, Inc. in US-VA-McLean

Job description

• We are seeking a highly skilled Senior AI Governance Analyst to lead the development, implementation, and oversight of governance frameworks that ensure our predictive and generative AI systems are safe, ethical, secure, and compliant with federal standards. The Senior AI Governance Analyst will serve as a subject-matter expert across responsible AI, policy compliance, risk management, and AI assurance throughout the lifecycle of AI solutions. This role partners closely with engineers, product teams, evaluators, and client stakeholders to embed governance principles into design, development, deployment, and ongoing operations.

Responsibilities

• Lead the development and implementation of AI governance frameworks aligned to federal policies, NIST AI Risk Management Framework, MLSecOps, agency-specific guidance, and emerging regulatory requirements.
• Drive AI risk identification, assessment, and mitigation processes, ensuring that generative and predictive AI systems adhere to ethical, legal, and security standards.
• Oversee the creation and maintenance of AI documentation artifacts such as model cards, data cards, lineage records, impact assessments, and system risk profiles.
• Collaborate with engineering and product teams to embed privacy, fairness, transparency, and explainability considerations into the design and operation of AI systems.
• Partner with AI Evaluation Scientists to establish governance-aligned quality thresholds, safety checks, and ongoing monitoring requirements for model outputs.
• Support compliance activities related to data usage, provenance, confidentiality, prompt injection defense, and secure model interaction patterns.
• Develop governance review processes, including AI readiness assessments, model approval workflows, and continuous assurance procedures.
• Conduct research on emerging AI regulatory trends, industry standards, federal mandates, and best practices, advising leadership on their implications.
• Communicate governance requirements and findings to diverse audiences, ensuring that stakeholders across programs understand risks, constraints, and recommended controls.
• Mentor junior analysts and contribute to the creation of templates, playbooks, and reusable assets that strengthen Steampunk’s AI governance capabilities.
• You will contribute to the growth of our AI & Data Exploitation Practice!

Requirements

• Ability to hold a position of public trust with the U.S. government.
• Bachelor’s, Master’s, or Ph.D. in Public Policy, Computer Science, Law, Cybersecurity, Data Ethics, or a related field.
• 5+ years of experience in AI governance, risk management, data ethics, compliance, or responsible technology roles.
• Strong understanding of federal policies, standards, and frameworks related to AI, including NIST AI RMF, EO 14110, OMB AI guidance, MLSecOps, privacy law , and agency-level directives.
• Demonstrated experience embedding governance controls into AI/ML development workflows, including documentation, reviews, and lifecycle risk management.
• Familiarity with LLMs, RAG systems, and generative AI architectures, and an ability to assess risks across these technologies.
• Experience conducting algorithmic impact assessments, model risk assessments, or responsible AI reviews.
• Strong communication skills with the ability to clearly articulate governance requirements to engineers, product teams, executives, and government clients.
• Ability to analyze technical systems, identify risks, and recommend actionable mitigations grounded in policy and best practices.
• Exposure to evaluation techniques, fairness assessments, transparency documentation, or audit processes preferred.
• Experience working in agile environments, collaborating across cross-functional teams, and driving governance processes independently.

Skills

Required

• Strong communication skills
• Mentoring junior analysts
• NIST AI RMF
• EO 14110
• OMB AI guidance
• MLSecOps
• Privacy law
• LLMs
• RAG systems
• Generative AI architectures
• Algorithmic impact assessments
• Model risk assessments