Agentic AI Engineer - Production LLM Systems

Blencorp; United States; On-site; USD 130,000 - 200,000; Full time

Benefits offered by this job

Competitive salary

Medical, dental, vision insurance

401(k) retirement plan

Professional development opportunities

Remote work options

Company-provided technology and tools

Job summary

BLEN is seeking an AI Engineer to design and ship agentic AI systems powering federal and commercial solutions. You will build multi-step agents, integrate MCP servers, and connect models to client data and tools.

The role emphasizes practical production engineering over pure research and involves collaborating with cross-functional teams to deliver rapid, safe AI capabilities. You will work on RAG pipelines, evals, observability, and tool use with a focus on responsible AI practices in

Qualifications

• 5+ years of professional software engineering with production AI features.
• Experience designing agentic systems with tool-calling and planning loops.
• Strong Python and back-end services development experience.
• Familiarity with MCP and agent/tool standards.
• Experience with RAG, embeddings, and vector stores.
• Experience with evals and observability for AI features.
• Knowledge of cloud platforms (AWS, Azure, or GCP).
• Ability to communicate AI trade-offs to non-technical stakeholders.

Responsibilities

• Design and build agentic systems with multi-step reasoning and human-in-the-loop checkpoints.
• Ship LLM-powered applications such as copilots, document intelligence, and workflow automation.
• Develop MCP servers and clients for secure data exposure to LLMs.
• Build and maintain RAG pipelines and grounding.
• Integrate model APIs (OpenAI, Anthropic, Bedrock, Azure OpenAI, open-weight models).
• Develop evals and observability for production AI features.

Skills

Python

LLM integration

Agentic systems

MCP

Distributed systems

Back-end APIs

Cloud platforms

Tools

FastAPI

Kubernetes

LangSmith

vLLM/Ollama

Git

SQL

Job description

BLEN is seeking an AI Engineer to design and ship agentic AI systems powering federal and commercial solutions. You will build multi-step agents, integrate MCP servers, and connect models to client data and tools.

The role emphasizes practical production engineering over pure research and involves collaborating with cross-functional teams to deliver rapid, safe AI capabilities. You will work on RAG pipelines, evals, observability, and tool use with a focus on responsible AI practices in