BLEN

BLEN

BLEN, Inc. is a veteran-owned digital agency in Washington D.C., specializing in cutting-edge digital solutions for federal agencies, non-profits, and enterprises. They excel in Application and Software Development, Website Development, and Visual Comm...

Internet Software & Services
11-50
Founded 2004

Description

  • Design and build agentic systems that plan, call tools, retrieve context, and take actions with human-in-the-loop checkpoints.
  • Build MCP servers and clients to securely expose client data, internal tools, and APIs to LLMs in a standardized and auditable way.
  • Ship LLM-powered applications such as copilots, document intelligence, search, summarization, and workflow automation tools.
  • Design and maintain RAG pipelines, including chunking, embeddings, vector stores, retrieval, reranking, and grounding.
  • Integrate model APIs from providers such as OpenAI, Anthropic, Bedrock, Azure OpenAI, and open-weight models, selecting the right model based on quality, latency, and cost.
  • Develop evals and observability for agents and AI features to monitor production performance and regressions.
  • 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 stakeholders to define what AI should and should not do in a product.
  • Help shape responsible AI practices for federal use, including privacy, security, auditability, and human oversight.

Requirements

  • 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 such as tool calling, multi-step reasoning, planning loops, or agent orchestration.
  • Working knowledge of the Model Context Protocol (MCP), or demonstrated ability to learn it quickly.
  • Strong Python experience and experience building and deploying backend services and APIs such as FastAPI or Flask.
  • Hands-on experience with at least one major LLM provider, such as OpenAI, Anthropic, Bedrock, Azure OpenAI, Vertex, or open-weight models via vLLM/Ollama.
  • Working knowledge of RAG, including embeddings, vector databases, and retrieval evaluation.
  • Comfort with prompt engineering, structured outputs, and tool/function calling.
  • Experience writing evals for non-deterministic systems, even lightweight ones.
  • Solid SQL experience and experience with relational and unstructured data.
  • Familiarity with at least one cloud platform, such as AWS, Azure, or GCP.
  • Strong written and verbal communication skills for explaining AI tradeoffs to non-technical stakeholders.
  • Experience authoring MCP servers for non-trivial systems, such as databases, internal APIs, or document stores, is preferred.
  • Experience with eval and observability platforms such as Braintrust, LangSmith, Langfuse, Arize, or custom harnesses is preferred.
  • Multi-agent orchestration experience and familiarity with agent failure modes is preferred.
  • Fine-tuning, distillation, or LoRA experience where it made a meaningful impact is preferred.
  • Docker, Kubernetes, and CI/CD experience for AI workloads is preferred.
  • TypeScript/Node experience for full-stack AI features is preferred.
  • Experience with streaming UIs and token-level UX patterns is preferred.
  • Experience with caching, prompt compression, and cost/latency optimization at scale is preferred.
  • Background supporting federal or government clients is preferred.
  • Awareness of NIST AI RMF, FedRAMP, or related responsible-AI frameworks is preferred.
  • 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.

Benefits

  • Work from anywhere in the United States.
  • Competitive pay with a salary range of $130,000 to $150,000 per year.
  • Contribution toward health benefits.
  • High-visibility federal projects with real impact.
  • Small team environment where ideas can ship quickly.
  • Generous exposure to the latest AI tooling and models.
  • Opportunity for personal and professional growth.
  • A fair, honest, and supportive team culture.

Interested in this position?

Apply directly on the company website

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