AI Strategy & Governance Leader

Accenture Federal Services•Washington, DC

12h

About The Position

At Accenture Federal Services, our purpose is to help the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations. Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more. Join us to drive positive, lasting change that moves missions and the government forward! You’ll lead (or contribute to) enterprise AI & data strategy for confidential federal programs shaping architecture, governance, and responsible AI so modern AI capabilities can be operated safely, audited confidently, and adopted at scale. This is a strategy + build + operate role: you’ll partner with CXOs, CDO/CIO/CISO offices, legal/compliance, security, and product teams to define standards, implement controls, and accelerate mission outcomes. Not a model‑training role. Your focus is production strategy, governance, and architecture making the best models and platforms usable, safe, and effective in real operations.

Requirements

Experience developing AI or data strategy or platform governance within government or multi stakeholder environments.
Strong understanding of federal policies related to data, AI, privacy, cybersecurity, and digital modernization.
Expertise in enterprise architecture concepts and AI governance frameworks.
Ability to communicate complex technical concepts to non-technical audiences.
Proven track record turning strategy into operational systems with measurable outcomes.
Experience assessing AI readiness, risks, and ethical considerations.
Must be a US Citizen

Nice To Haves

Experience in regulated/secure environments (audit‑ready controls, ATO like processes, Zero Trust concepts).
Exposure to LLM evaluation frameworks, RAG/agent patterns, prompt lifecycle management, and policy‑based filtering.
Familiarity with leading platforms/services like Azure/AWS/GCP, Databricks/Snowflake/Palantir, vector search, catalog/lineage tooling.
Contributions to playbooks/standards or open‑source; executive‑level storytelling and proposal leadership.

Responsibilities

Translate mission goals into portfolio roadmaps, target architectures, and adoption plans; pick the right patterns (LLM, RAG, agents, analytics) for each use case.
Define reference architectures (cloud/hybrid/on‑prem), data access patterns, metadata/lineage, and integration points that respect Zero Trust and privacy constraints.
Operationalize policy‑as‑code, approval workflows, audit trails, red‑team & safety checks, and model/data lifecycle controls aligned to federal standards.
Stand up evaluation harnesses (quality, safety, latency, cost), model selection criteria, and guardrails (prompt management, filtering, attribution/citations).
Author playbooks, templates, SDKs, and governance blueprints that scale across multiple mission teams driving consistency and speed.
Partner with product, security/compliance, data, and engineering to deliver outcomes; facilitate decision forums and executive storytelling with measurable KPIs.
Ensure programs meet SLOs (reliability, latency, safety, cost), pass audits, and ship in weeks not quarters with progressive delivery in regulated environments.
Contribute to proposals, briefings, and internal capability building; mentor teams on responsible AI and governed data practices