Note: The job is a remote job and is open to candidates in USA. Accenture Federal Services is a technology company serving U.S. federal government missions across defense, national security, public safety, civilian, and military health. The Generative AI Applications Engineer will build and operate secure, reliable, and scalable generative AI applications, focusing on agentic workflows, retrieval-augmented generation, prompt and policy design, evaluation, platform integration, and production operations.
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
- * Built and deployed a production GenAI application (chatbot, copilot, assistant, or enterprise AI)
- * Hands-on with LLMs GPT, Claude, Llama, Gemini, Mistral, via APIs or self-hosted
- * Designed and implemented RAG solutions using embeddings, vector databases, and semantic search for enterprise or mission data
- * Shipped AI applications with frameworks like LangChain, LangGraph, LlamaIndex, Semantic Kernel, DSPy, or similar
- * Strong Python development for building and integrating AI/ML applications
- * Owned AI solutions through full production life cycle, deployment and operational support
- * Active 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
- *Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.*
Benefits
- Hands-on experience
- Certifications
- Industry training
- Hands-on growth
Company Overview