Generative AI Applications Engineer; Agents & RAG

Position: Generative AI Applications Engineer (Agents & RAG)
At Accenture Federal Services, nothing matters more than helping 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!

** Build AI that matters** . We ship production GenAI apps for confidential federal programs across defense, national security, public safety, civilian, and military health where reliability, privacy, and safety aren't optional. AFS is a technology company within global Accenture and a Glassdoor Top 100 Best Place to Work. You'll join a collaborative, inclusive community with handson growth, certifications, and industry training.

We ship in weeks, not quarters, and measure success with latency, reliability, safety, and cost.

** Confidentiality matters:
** We don't disclose program details publicly. If you advance, we'll share specifics during the process.

** Role Overview*
* You'll turn mission needs into secure, reliable, and scalable GenAI applications no model training required. This is a hands-on role across agentic workflows, RAG, prompt/policy design, LLM evaluation, and platform integration. You'll own the end-to-end path from use case evaluation → production deployment → operational excellence, partnering with product, security, data, and SRE to ship features safely and at scale.

** What You'll Do (Day to Day)*
* + 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 Lang Chain/Llama Index/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, Open Search, 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 & Fin Ops 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.

** You'll Thrive Here If you have*
* + 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, Open Search, pgvector, FAISS/Chroma) and grounding AI in enterprise/mission data.

+ U.S. Citizenship

** Nice to Have*
* + 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…