Role OverviewDefine and deliver AI-enabled products that connect mission needs to measurable outcomes. You'll set vision, strategy, and roadmaps, translate stakeholder requirements into clear, testable work, and lead cross-functional teams data, AI, engineering, policy, security to ship in weeks, not quarters. You'll embed Responsible AI and governance by design so products are trusted, auditable, and adoptable at scale.
Product strategy, governance, and delivery not foundation model training. Your craft is turning the best models and platforms into safe, reliable, user-loved experiences.
What You'll Do- Translate mission goals into product KPIs (adoption, latency, reliability, safety, cost) build outcome-based roadmaps and investment cases.
- Convert ambiguous needs into prioritized user stories and release plans; run MVPs, A/B tests, and progressive delivery in regulated environments.
- Operationalize policy-as-code, prompt version lifecycle, guardrails (filtering, citations), human-in-the-loop flows, and audit trails aligned to federal standards.
- Collaborate with architects to choose the right patterns (LLM, RAG, agents, analytics), data access models, and Zero Trust integrations across cloud/hybrid/on-prem.
- Stand up evaluation harnesses (helpfulness, safety, factuality), define SLIs/SLOs (quality, latency, cost), and drive incident/postmortem rigor to reduce MTTR.
- Align business owners, CDO/CIO/CISO/legal/compliance; run decision forums; tell the story with clear value/risk frameworks.
- Author playbooks, templates, and product operating models that scale across multiple mission teams; mentor PMs and cross-functional leads.
- Ensure products meet SLOs, pass audits, and work in real-world constraints (hybrid, restricted, or air-gapped environments).
Requirements- Delivered AI and data powered products at enterprise scale, generating measurable business results and mission impact.
- Backlog management, roadmap ownership, KPI definition, experimentation (MVPs/A/B), and iterative releases that improve time-to-value.
- Practical experience embedding guardrails, privacy/security controls, and auditability into product delivery.
- Comfortable partnering with engineering, data/AI, security/compliance, policy/operations
- Able to reason about LLM orchestration, RAG/agents, data/platform architecture, and evaluation hands-on enough to review designs and validate solutions.
- Proven ability to turn strategy into production systems with measurable adoption and reliability.
- U.S. Citizen (no dual citizenship)
Nice to Have- Experience in regulated/secure environments audit-ready controls, ATO-like processes, STIGs and Zero Trust.
- Familiarity with platforms/services such as Azure, AWS, GCP, Databricks, Snowflake, Palantir, vector search, catalog/lineage tooling.
- Exposure to LLM evaluation frameworks, prompt lifecycle management, policy-based filtering, and agent workflows.
- Contributions to product playbooks/standards or open-source; executive-level storytelling and proposal support.
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of
California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
The pay range for the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland is:
$114,000-$221,000 USD
