[Remote] Generative AI Applications Engineer (Agents & RAG)
Note: The job is a remote job and is open to candidates in USA. Accenture Federal Services is dedicated to helping the US federal government enhance national security and improve people's lives. The Generative AI Applications Engineer will develop secure and scalable GenAI applications, focusing on mission needs and working collaboratively across various teams to ensure successful deployment and operational excellence.
Responsibilities
- Design & ship mission grade GenAI: Build agentic workflows and RAG systems tailored to mission data and environments; target low hallucination, tight p95 latency, and predictable cost
- Agent frameworks & orchestration: Apply patterns from LangChain/LlamaIndex/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies
- Platform integration (no model training): Implement with AWS Bedrock, Azure OpenAI, Google Vertex AI, Amazon Kendra, and managed services (e.g., Document AI, Gemini, Gemma)
- LLM selection & evaluation: Compare models for quality, safety, latency, cost; author/test prompts & policies; deploy with observability and safe rollback/fallback
- RAG done right: Build retrieval pipelines & vector search (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise
- Production rigor: Instrument metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails
- SRE & FinOps for AI: Define SLIs/SLOs (quality/latency/safety/cost), run on call and postmortems, reduce MTTR; meter usage and optimize token/spend
- Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off projects
- Operate in real world constraints: Deliver into hybrid, restricted, or air gapped environments with Zero Trust principles and audit ready controls
Skills
- End-to-end ownership of production systems: integration → deployment → observability → incident response
- Hands-on experience with LLMs, transformer based apps, and RAG in production
- Strong Python
- Experience with vector search and retrieval (Pinecone, Weaviate, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data
- U.S. Citizenship
- Integration with leading cloud AI services or on prem inference stacks
- Background in LLM evaluation, prompt authoring/testing, A/B experimentation, and LLM Ops
- Responsible AI expertise (privacy, security, bias, transparency, human in the loop) and data governance
- Experience implementing tool using agents for API integration and external data access
- Containerization & orchestration (Docker, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell)
- Prior work in regulated/secure environments (e.g., ATO, STIGs, Zero Trust) with fast shipping
- Familiarity with NVIDIA AI Foundations, OpenAI ChatGPT, and AI assisted dev tools (Cursor, Windsurf, Claude)
- Contributions to internal frameworks or opensource; mentorship of engineers
- Clear communication with engineers, PMs, and security/compliance stakeholders
Benefits
- Certifications
- Industry training
- Hands-on experience
- Accenture Federal Services offers a wide variety of benefits. [You can find more information on benefits here.](https://www.accenture.com/us-en/careers/your-future-rewards-benefits)
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