Sr. AI Software Engineer - Agent Harness

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About the position

Our Mission At Intel, our journey is to transform AI into something safer, more trustworthy, and respectful of human privacy by design. We believe transformative AI should have a positive impact on people—powerful in capability, yet honest about its limits and protective of the data and resources it touches. To get there, we build agentic AI that combines the best of local and cloud intelligence — private, affordable, and sustainable by design. Small, efficient models run directly on the user's machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while powerful cloud models handle the hardest work: planning, reasoning, and complex problem-solving. Today, neither approach can deliver this alone. Together, they give people real capability without compromise—data stays private, spend stays predictable, and energy use stays in check. We're building intelligence that scales without sacrificing trust, cost, or the planet—because the future of AI should belong to the people it serves. Role Summary: The model is only half an agent; the harness is the other half. You build everything around the model that makes it act — context management, tool and function calling, file and terminal execution, scheduling, memory, and the agent loop itself. This is core product engineering on an agent framework comparable to well know AI models, but built to run hybrid (local + cloud) and with efficiency.

Responsibilities

  • Design and build the agent loop: planning, tool invocation, observation handling, retries, termination
  • Implement tool integrations — file I/O, terminal / shell execution, web, MCP servers, message apps
  • Build context management: what goes in the window, when to summarize, how to use long / cross-session memory
  • Implement scheduling and automatic / background task execution
  • Keep the harness model-agnostic so local and cloud models are swappable behind one abstraction
  • Design agent security mechanisms through different approaches
  • Make the loop observable, debuggable: tracing, replay, and reproducible agent sessions

Requirements

  • BS/MS in CS, EE, Math or related STEM field
  • 8+ years software development background
  • Strong command of Python, TypeScript, Go, Rust, C++
  • Expertise with async, concurrency, and process / subprocess management
  • Experience with projects that calls external tools or APIs in a loop and handled the failure modes
  • Experienced at reading unfamiliar codebases and someone else’s runtime

Nice-to-haves

  • Experience with agent frameworks, tool / function calling, or MCP
  • Built developer tooling, CLIs, or IDE-adjacent products
  • Familiarity with sandboxing, containerization, and safe code execution
  • Contributions to open-source agent / LLM tooling
  • Experience with agent security

Benefits

  • competitive pay
  • stock bonuses
  • health
  • retirement
  • vacation
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