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Requirements and responsibilities
About BLENBLENers are passionate about using technology to solve real-world problems. For over 20 years, we've helped government agencies and businesses transform their digital experience — modernizing legacy systems, building cloud-native applications, and experimenting with what's just around the corner. We value long, enduring partnerships and put humans at the center of every experience. Our team thrives on turning tricky problems into solutions that are practical, accessible, and performant.About this positionWe're hiring an AI Engineer to help our federal and commercial clients ship production-grade applications powered by large language models — with a strong focus on agentic systems and MCP-based integrations.You'll spend your time building real things: agents that take actions on behalf of users, RAG pipelines that ground answers in trusted sources, and MCP servers that securely connect models to the data and tools our clients already rely on. You'll wire up model APIs, design tool interfaces, build evals, and make sure what we ship is fast, reliable, observable, and safe.This isn't a research role. You won't be training foundation models. You will be designing and shipping agentic AI systems that real users — including senior government stakeholders — depend on, and you'll have a strong voice in how we adopt generative AI responsibly across our portfolio.If you get excited about agent design, tool use, MCP, evals, and the weekly firehose of new models and frameworks — and you want that energy pointed at meaningful public-sector work — this is for you.What You'll DoDesign and build agentic systems — multi-step agents that plan, call tools, retrieve context, and take action with appropriate human-in-the-loop checkpointsBuild MCP servers and clients to securely expose client data, internal tools, and APIs to LLMs in a standardized, auditable wayShip LLM-powered applications: copilots, document intelligence, search, summarization, and workflow automationDesign and maintain RAG pipelines — chunking, embeddings, vector stores, retrieval, reranking, and groundingIntegrate model APIs (OpenAI, Anthropic, Bedrock, Azure OpenAI, open-weight models) and pick the right model for the job based on quality, latency, and costDevelop evals and observability for agents and AI features so we know what's working in production and what's regressingApply prompt engineering, structured outputs, function/tool calling, and guardrails to make agent behavior predictableWrite production Python backends and APIs that expose AI capabilities to web and mobile clientsCollaborate with engineers, designers, and product folks to scope what AI should (and shouldn't) do in a given productHelp shape responsible AI practices for federal use — privacy, security, auditability, and human oversightBasic qualifications5+ years of professional software engineering experience, with at least 1 year shipping LLM-based or AI-powered features to productionHands-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 standardsStrong 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 evaluationComfort with prompt engineering, structured outputs (JSON mode, schemas), and tool/function callingExperience writing evals — even lightweight ones — for non-deterministic systemsSolid SQL and experience with relational and unstructured dataFamiliarity with at least one cloud platform (AWS, Azure, or GCP)Git, code review, and modern collaborative workflowsStrong written and verbal communication — you can explain AI tradeoffs to non-technical stakeholdersNice to HaveExperience 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 modesFine-tuning, distillation, or LoRA experience where it actually moved the needleDocker, Kubernetes, and CI/CD for AI workloadsTypeScript/Node for full-stack AI featuresStreaming UIs (SSE, WebSockets) and token-level UX patternsExperience with caching, prompt compression, and cost/latency optimization at scaleBackground supporting federal or government clientsAwareness of NIST AI RMF, FedRAMP, or related responsible-AI frameworksRequirementsMust be a US Citizen or legal resident, able to work domesticallyMust be able to attain a low-level security clearanceMust work from the United StatesPerksWork from anywhere in the USCompetitive payContribution toward health benefitsHigh-visibility federal projects with real impactSmall team where your ideas actually shipGenerous exposure to the latest AI tooling and modelsGet to know usWe're a small, creative, highly technical team. Our heroes are the scrappy folks who dare to dream and do great things. We care more about doing the right thing than taking shortcuts. We finish projects. We surprise our clients with how much we genuinely care about their success. We're selective about our partners — and our people. We don't say "human resource" because you're not a resource. You're a teammate, and we'll treat you like one.What you should expect from usWe will treat you fairlyWe give you space to grow personally and professionallyWe will hear your ideas even when we disagreeWe will be honest about our challenges and equitable with our successWe will tell you the truth, even when it's difficult$130,000 - $150,000 a yearThis range represents the compensation we expect to offer candidates who can perform the core responsibilities with minimal additional training. Actual compensation may vary based on skill set, experience, certifications, and scope of responsibility.Equal OpportunityBLEN is an Equal Opportunity Employer / Protected Veterans / Individuals with Disabilities.We may use AI tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are made by humans.We participate in E-Verify. Upon hire, we will provide the federal government with your Form I-9 information to confirm authorization to work in the U.S. Due to the nature of our federal work, all BLEN roles must be performed from the contiguous United States.We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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