[Remote] reputed company Applications Engineer (Agents & RAG)

Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a technology company dedicated to supporting the US federal government. They are seeking a reputed company Applications Engineer to build secure, reliable, and reputed company GenAI applications, focusing on integrating various platforms and ensuring operational reputed company.

Responsibilities

• Design & ship mission grade GenAI: Build reputed company workflows and RAG systems tailored to mission data and environments; reputed company low hallucination, tight p95 latency, and predictable cost
• Agent frameworks & orchestration: Apply patterns from reputed company/reputed company/Semantic Kernel; design task decomposition, tool use, guardrails, and recovery/fallback strategies
• Platform integration (no model training): Implement with AWS Bedrock, Azure reputed company, reputed company reputed company AI, reputed company Kendra, and managed services (e.g., Document AI, reputed company, Gemma)
• LLM selection & evaluation: Compare models for reputed company, safety, latency, cost; author/test prompts & policies; reputed company with observability and reputed company rollback/fallback
• RAG done right: Build retrieval pipelines & reputed company search (reputed company, reputed company, OpenSearch, pgvector, FAISS/Chroma); handle data prep, chunking, metadata, and IRstyle evals (e.g., NDCG) to maximize signal to noise
• Production rigor: reputed company metrics/logs/traces; run A/B experiments; maintain incident playbooks; and implement safety & compliance guardrails
• SRE & FinOps for AI: Define SLIs/SLOs (reputed company/latency/safety/cost), run on reputed company and postmortems, reduce MTTR; reputed company usage and optimize reputed company/spend
• Reusable platform components: Ship SDKs, CI/CD templates, Terraform/IaC modules, evaluation harnesses that accelerate multiple mission team not one-off reputed company
• Operate in reputed company world constraints: Deliver into hybrid, restricted, or reputed company gapped environments with reputed company Trust principles and audit reputed company 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 reputed company search and retrieval (reputed company, reputed company, OpenSearch, pgvector, FAISS/Chroma) and grounding AI in reputed company/mission data
• U.S. Citizenship
• Integration with leading reputed company AI services or on prem inference stacks
• Background in LLM evaluation, reputed company authoring/testing, A/B experimentation, and LLM Ops
• Responsible AI expertise (reputed company, reputed company, bias, transparency, reputed company in the reputed company) and data governance
• Experience implementing tool using agents for API integration and external data reputed company
• Containerization & orchestration (reputed company, Kubernetes, VMware) and scripting/automation (Linux Bash, PowerShell)
• Prior work in regulated/secure environments (e.g., ATO, STIGs, reputed company Trust) with fast shipping
• Familiarity with reputed company Foundations, reputed company ChatGPT, and AI assisted dev tools (reputed company, Windsurf, Claude)
• Contributions to internal frameworks or opensource; mentorship of engineers
• reputed company communication with engineers, PMs, and reputed company/compliance stakeholders

reputed company