Accenture Federal Services
Generative AI Applications Engineer (Agents & RAG)
About this role
Accenture Federal Services seeks a Generative AI Applications Engineer to build secure, production-grade AI applications for federal government missions. You'll design agentic workflows and RAG systems, handling everything from use-case evaluation through deployment and operational excellence.
What you'll do
- Design and deploy mission-grade generative AI applications including agentic workflows and RAG systems
- Evaluate LLMs and optimize prompt/policy design for low hallucination and tight latency
- Own end-to-end delivery from use-case assessment through production deployment
- Collaborate with product, security, data, and SRE teams to ship features safely at scale
- Monitor operational excellence and ensure reliability, privacy, and safety standards
- Integrate AI solutions with existing platforms and government environments
What they're looking for
- Generative AI and large language models (LLMs)
- Agentic AI workflows and design patterns
- Retrieval-augmented generation (RAG)
- Prompt engineering and policy optimization
- Python or similar backend programming languages
- Cloud platforms and infrastructure
- System design and scalability
- Security and compliance in federal environments
Benefits
- Glassdoor Top 100 Best Place to Work recognition
- Hands-on growth opportunities and professional certifications
- Industry training and development programs
- Collaborative and inclusive community
- Fast-paced environment shipping in weeks
- Impact on national security and federal missions
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Accenture Federal Services
Accenture Federal Services builds and maintains mission-critical technology solutions for the U.S. federal government, including cloud infrastructure, enterprise systems integrations, and cyber defense tools. The company is hiring DevOps engineers, full-stack developers, SAP specialists, and test engineers to support classified and unclassified federal government projects.
- Website
- accenturefederal.com
Likely interview questions
- Walk us through how you've designed a RAG system from scratch—what retrieval strategy did you choose, and how did you evaluate hallucination and relevance?
- Describe your experience building agentic workflows. How did you handle tool selection, error recovery, and preventing infinite loops?