Note: The job is a remote job and is open to candidates in USA. BLEN is a company passionate about using technology to solve real-world problems. They are seeking an AI Engineer to help federal and commercial clients develop production-grade applications powered by large language models, focusing on agentic systems and MCP-based integrations.
Responsibilities
- Design and build agentic systems — multi-step agents that plan, call tools, retrieve context, and take action with appropriate human-in-the-loop checkpoints
- Build MCP servers and clients to securely expose client data, internal tools, and APIs to LLMs in a standardized, auditable way
- Ship LLM-powered applications: copilots, document intelligence, search, summarization, and workflow automation
- Design and maintain RAG pipelines — chunking, embeddings, vector stores, retrieval, reranking, and grounding
- Integrate model APIs (OpenAI, Anthropic, Bedrock, Azure OpenAI, open-weight models) and pick the right model for the job based on quality, latency, and cost
- Develop evals and observability for agents and AI features so we know what's working in production and what's regressing
- Apply prompt engineering, structured outputs, function/tool calling, and guardrails to make agent behavior predictable
- Write production Python backends and APIs that expose AI capabilities to web and mobile clients
- Collaborate with engineers, designers, and product folks to scope what AI should (and shouldn't) do in a given product
- Help shape responsible AI practices for federal use — privacy, security, auditability, and human oversight
Skills
- 5+ 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 — tool calling, multi-step reasoning, planning loops, or agent orchestration (LangGraph, CrewAI, OpenAI Agents SDK, Claude tool use, or equivalent)
- Working knowledge of the Model Context Protocol (MCP) — or demonstrated ability to pick it up quickly, plus familiarity with the broader landscape of agent/tool standards
- Strong Python and experience building and deploying backend services and APIs (FastAPI, Flask, or similar)
- Hands-on experience with at least one major LLM provider (OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex, or open-weight models via vLLM/Ollama)
- Working knowledge of RAG: embeddings, vector databases (pgvector, Pinecone, Weaviate, Qdrant, or similar), and retrieval evaluation
- Comfort with prompt engineering, structured outputs (JSON mode, schemas), and tool/function calling
- Experience writing evals — even lightweight ones — for non-deterministic systems
- Solid SQL and experience with relational and unstructured data
- Familiarity with at least one cloud platform (AWS, Azure, or GCP)
- Git, code review, and modern collaborative workflows
- Strong written and verbal communication — you can explain AI tradeoffs to non-technical stakeholders
- Must be a US Citizen or legal resident, able to work domestically
- Must be able to attain a low-level security clearance
- Must work from the United States
- Experience authoring MCP servers for non-trivial systems (databases, internal APIs, document stores)
- Experience with eval and observability platforms (Braintrust, LangSmith, Langfuse, Arize, or custom harnesses)
- Multi-agent orchestration patterns and experience reasoning about agent failure modes
- Fine-tuning, distillation, or LoRA experience where it actually moved the needle
- Docker, Kubernetes, and CI/CD for AI workloads
- TypeScript/Node for full-stack AI features
- Streaming UIs (SSE, WebSockets) and token-level UX patterns
- Experience with caching, prompt compression, and cost/latency optimization at scale
- Background supporting federal or government clients
- Awareness of NIST AI RMF, FedRAMP, or related responsible-AI frameworks
Benefits
- Work from anywhere.
- The chance to work on high-visibility projects and make a significant impact.
- Comprehensive medical, dental, vision, life, and disability insurance.
- Up to 20+ days of PTO annually.
- 401(k) retirement savings plan.
- FSA/HSA and commuter benefit options.
- Professional development opportunities, certifications, and continuous learning support.
- Company-provided technology and access to productivity and AI tools.
- Additional bonus based on performance.
Company Overview