Software Engineer - Agent Harness

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
• This role builds the harness. Shipping and running it reliably in production is owned by the SRE / Production squad - you partner with them; you don't carry the pager.
• What you'll learn / grow into
• Curiosity is required. You will develop:
• How frontier agent harnesses are architected - and how to do it efficiently.
• hybrid model routing and graceful degradation
• The hard parts: context-window economics, tool-call reliability, and multi-agent orchestration
• Interest in LLM agents and how they actually work under the hood
• IMPORTANT:
• Please be informed that Intel is proactively trying
• to find candidates for this position which is frequently available
• at Intel.
• Please note that the position may not be available
• at this time. If you would be interested in this position should it
• become available, we would encourage you to apply, and our
• hiring team will be glad to contact you when/if relevant.

Requirements

• Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
• You must possess the minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
• Required Qualifications
• BS/MS in CS, EE, Math or related STEM field
• 5+ years software development background
• Strong in at least one of Python, TypeScript, Go, Rust, C++
• Comfortable with async, concurrency, and process / subprocess management
• Has built a project that calls external tools or APIs in a loop and handled the failure modes
• Experienced at reading unfamiliar codebases and someone else's runtime
• 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
• Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.
• Benefits at Intel
• Job Type:
• Shift:
• Shift 1 (United States of America)
• Primary Location:
• US, California, Santa Clara
• Additional Locations:
• US, Arizona, Phoenix, US, California, Folsom, US, Oregon, Hillsboro
• Business group:
• The Client Computing Group (CCG) is responsible

Benefits

Additional Information

Job Details: Job Description: 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.

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