IMC is embedding agentic AI directly into the developer workflow for our production-critical systems. As a member of the Agentic AI engineering team, you’ll help build agents, MCP servers, and evaluation loops that make AI-generated code reliable, auditable, and fast to ship. You’ll work closely with experienced engineers and platform teams to deliver pragmatic, high-impact AI integrations at scale.
What You’ll Do
• Contribute to the platform by implementing agents, MCP servers, and supporting services that propose and apply changes to large codebases
• Assist in developing retrieval systems that give AI agents and developers accurate, up-to-date context from large codebases and design artifacts
• Help measure and improve AI-generated changes by building compile/test/evaluate pipelines (static analysis, style and safety checks, performance gates, code review)
• Apply IMC’s best practices in concurrency, telemetry, configuration hygiene, and performance-sensitive code paths to ensure AI outputs are reliable and idiomatic
• Collaborate with teammates on experiments to evaluate and improve AI-driven workflows
What You Bring
• BS+ in Computer Science (or related) with strong fundamentals (algorithms, data structures, systems)
• Proficiency in a high-level programming language (Java or Python preferred)
• Experience contributing to developer-facing or production systems
• Curiosity and eagerness to learn about AI/LLM application patterns, even if you haven’t worked closely with them yet
• Strong communication skills; comfortable working with engineers in a fast, collaborative environment
Nice to Have
• Exposure to AI tools or workflows (e.g., LangChain, LangGraph, AutoGen, or similar)
• Experience with retrieval systems (vector search, embeddings, or hybrid approaches)
• Familiarity with compiler/static analysis or large-scale refactoring tools
• Interest in customizing or fine-tuning open-weight models
• Knowledge of model-serving or evaluation infrastructure
Why Th