AI Engineer

The Opportunity

As an AI engineer, you’ll design and deliver production-grade AI systems. You’ll own RAG pipelines, evaluation systems, and performance optimization leveraging modern AI infrastructure and tooling to build scalable, observable, and efficient services. You'll work across the full AI application lifecycle from enterprise data ingestion and retrieval to prompt engineering, evaluation, deployment, observability, and production operations building secure, scalable AI solutions for mission-critical federal environments.

You Have

• 3+ years of experience building production systems, including AI / ML applications
• Experience building LLM systems using RAG frameworks such as LangChain and LlamaIndex, or custom pipelines and vector stores with Pinecone, Weaviate, FAISS, or OpenSearch Vector Search
• Experience designing embedding pipelines, including document ingestion, chunking strategies, indexing, met adata filtering, retrieval optimization, and hybrid search, and designing APIs and services using FastAPI, Flask, or Node.js
• Experience with cloud-native architectures, including AWS services such as Bedrock, SageMaker, EKS or ECS, S3, IAM, Lambda, CloudWatch, and Secrets Manager, and agent frameworks and orchestration patterns such as LangGraph, tool calling, and function calling APIs
• Experience implementing observability, including logging and tracing with OpenTele met ry, Datadog, or CloudWatch, and met rics pipelines tracking latency, throughput, token usage, cache hit rate, and error rates
• Experience optimizing performance using caching layers such as Redis, parallelization or async workflows, and chunking and retrieval tuning, and designing automated evaluation pipelines using benchmark datasets, LLM-as-a-judge techniques, regression testing, and human evaluation workflows
• Experience supporting production AI services, including deployment, monitoring, incident response, debugging, and performance tuning, and managing