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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.

What you'll do:

• 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.

Qualifications:Job Type:Shift:Shift 1 (United States of America)Primary Location: US, California, Santa ClaraAdditional Locations:US, Arizona, Phoenix, US, California, Folsom, US, Oregon, HillsboroPosting Statement:All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.Position of TrustN/ABenefits

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.

Annual Salary Range for jobs which could be performed in the US: $195,200.00-361,200.00 USDThe range displayed on this job posting 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. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.

Work Model for this Role

This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.

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ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.