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Forward Deployed AI Engineer

Accenturefederalservices · Washington, DC

onsitesenior$70,500–$70,500Posted Sep 8, 2026PythonGenAIRAGAPIsData Pipelines

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About this role

**Forward Deployed AI Engineer** **About the APX Forward Deployed Engineer (FDE) Program** APX (Advanced Partnership Accelerator) is a Center of Excellence under Accenture Federal Services' Data & AI capability. The FDE Program is a strategic initiative to position AFS at the forefront of AI innovation in government. This program embeds elite technical talent directly with federal clients to accelerate adoption and implementation of frontier AI capabilities from leading laboratories including OpenAI, Anthropic, Google, and other cutting-edge AI partners. As an FDE, you will serve as the critical bridge between breakthrough AI technology and mission-critical federal applications. You'll work hands-on with the most advanced AI models available, translating their transformative potential into tangible value for defense, intelligence, civilian, and public health missions. **What You Will Do** **Lead and Drive Mission-Embedded Build Teams** • Serve as the technical lead working within federal client teams, guiding engineering decisions in fast, complex conditions • Architect, build, and deploy rapid prototypes using frontier AI tools and frameworks • Translate complex mission problems into actionable technical roadmaps and implementable designs • Support integration of AI-native solutions into diverse client environments, including legacy platforms and classified environments • Operate across the full tech stack with autonomy and engineering depth • Drive development of applications and workflows that interact with structured and unstructured enterprise data at scale **Lead AI Native Engineering Practices** • Leverage advanced GenAI tooling, agentic frameworks, and autonomous workflows as core components of daily engineering delivery • Design and implement sophisticated GenAI solutions such as RAG architectures, semantic search systems, and agentic orchestration • Evaluate model performance, improve generations and pipelines, and uphold responsible AI practices in mission-critical settings • Drive fast experimentation cycles with close operator feedback loops and rapid iteration

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