Sr. AI Software Engineer - Agent Harness

About the role

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.

The model is only half an agent; the harness is the other half. You will 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-known 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 and 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

• 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

Requirements

Minimum qualifications:

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

Preferred qualifications:

• 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 may be obtained through a combination of industry-relevant job experience, internship experiences, schoolwork, classes, or research.

Benefits

Our total rewards package goes above and beyond just a paycheck. Whether you're looking to build your career, improve your health, or protect your wealth, we offer generous benefits to help you achieve your goals. Benefits include competitive pay, stock bonuses, health programs, retirement plans, and vacation.

Pay

Annual Salary Range for jobs which could be performed in the US: $195,200.00 - $361,200.00 USD. The range reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Schedule

This role follows a hybrid work model, allowing employees to split their time between working on-site at their assigned Intel site and off-site.

Shift: Shift 1 (United States of America)

Locations

• US, California, Santa Clara
• US, Arizona, Phoenix
• US, California, Folsom
• US, Oregon, Hillsboro