AI Engineer
$130,000–$150,000 year
Remote · United States
Job Summary
AI Engineer for a federal/commercial-focused software firm building production-grade AI applications. Role involves designing and shipping agentic systems, MCP servers/clients, and RAG pipelines; implementing Python backends and APIs (FastAPI/Flask); integrating with major LLM providers (OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex); working with embeddings and vector stores (pgvector, Pinecone, Weaviate, Qdrant); building AI-powered features such as copilots, document intelligence, search, summarization, and workflow automation; writing evals for non-deterministic systems; ensuring observability and production readiness; collaborating with government stakeholders and adopting responsible AI practices. Requirements include 5+ years of software engineering, hands-on experience with agentic systems, MCP familiarity, strong Python, cloud experience (AWS/Azure/GCP), and clear communication.
Required Qualifications
- 5 or more years of professional software engineering experience with at least 1 year shipping LLM-based or AI-powered features to production
- Hands-on experience designing or building agentic systems using tool calling, multi-step reasoning, planning loops, or agent orchestration (LangGraph, CrewAI, OpenAI Agents SDK, Claude tool use, or equivalent)
- Working knowledge of MCP or demonstrated ability to pick it up quickly
- Strong Python and experience building and deploying backend services and APIs (FastAPI, Flask, or similar)
- Experience with at least one major LLM provider: OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex, or open-weight models
- Working knowledge of RAG: embeddings, vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar), and retrieval evaluation
- Comfort with prompt engineering, structured outputs, and tool/function calling
- Experience writing evals for non-deterministic systems
- Solid SQL and comfort with relational and unstructured data
- Familiarity with at least one cloud platform: AWS, Azure, or GCP
- Strong written communication -- you can explain AI tradeoffs to non-technical stakeholders
- Nice to have: Experience authoring MCP servers for non-trivial systems
- Eval and observability platform experience (Braintrust, LangSmith, Langfuse, Arize, or custom)
- Multi-agent orchestration and experience reasoning about agent failure modes
- Fine-tuning, distillation, or LoRA experience
- Docker, Kubernetes, and CI/CD for AI workloads
- TypeScript/Node for full-stack AI features
- Background supporting federal or government clients
- Awareness of NIST AI RMF, FedRAMP, or related responsible AI frameworks
Additional Requirements
- Must be a US citizen or legal resident, able to work domestically
- Must be able to attain a low-level security clearance
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