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Washington, D.C. / Hybrid
DevSecOps (3-5 yrs experience)
Red Hat Ansible (3-5 yrs experience)
Containerization (3-5 yrs experience)
AI Architecture (3-5 yrs experience)
As a software engineer, you will lead the development of our next-generation Agentic AI systems. Unlike traditional chatbots, you will build autonomous agents capable of reasoning, planning, and executing multi-step tasks to solve complex business problems.
You will be responsible for the entire lifecycle: from developing Retrieval-Augmented Generation (RAG) pipelines and orchestrating multi-agent workflows in Python, to provisioning scalable, secure AWS infrastructure using Terraform.
Design and implement autonomous AI agents using frameworks like LangGraph, CrewAI, or AutoGen. Develop custom logic for task decomposition, tool-use (function calling), and self-correction loops.
Build and optimize RAG pipelines to ground LLMs in enterprise data. This includes managing document chunking strategies, embedding models, and vector database integration (e.g., Amazon OpenSearch or Pinecone).
Develop robust, features in Python (Lambdas/FastAPI) to serve as the backbone for AI agents.
Infrastructure as Code (IaC): Use Terraform to manage all cloud resources, ensuring that environments (Dev, Staging, Prod) are reproducible, version-controlled, and secure.
Deploy and scale AI workloads using Amazon Bedrock, AWS Lambda, ECS/EKS, and S3.
Evaluation & Observability:Implement ""LLM-as-a-judge"" frameworks and tracing tools (e.g., LangSmith, DeepEval) to monitor agent reasoning, reduce hallucinations, and optimize token costs.
Work Location On-site (Government / AFS Site): Washington, D.C. / Hybrid
On-site %:40% (travel up to 25%)
Full-time
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