Agent Engineer
Posted 16 Oct 2026
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 5+ yrs
- Management level
- Individual contributor
- Employment
- Remote
- Contract
- Full-time
- Visa sponsorship
- Not offered
No salary listed for this role.
Field of studyEngineering
Study levelBachelor's
About the Role
Join an AI-powered productivity software team building dependable agent capabilities for real-world work. You will help turn advances in reasoning, planning, memory, and tool use into useful product experiences that users can trust.
What You'll Do
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Explore advances in agent technology and identify opportunities to solve user problems.
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Translate model capabilities into reliable, reusable skills and workflows.
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Build and evolve Python agent systems, including orchestration, context management, retries, and error recovery.
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Design integrations with email, calendars, messaging, browsers, documents, CRMs, and other business software.
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Own capabilities across Python services, Django, APIs, React interfaces, data models, background jobs, and production operations.
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Create platform abstractions that make capabilities easier to compose, extend, and maintain.
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Improve latency, cost, reliability, and safety in high-volume agent execution.
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Use evaluations, production traces, and user feedback to find and fix quality issues.
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Set technical direction for ambiguous problems and contribute to design reviews.
What We're Looking For
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At least 5 years of experience building and operating production software systems end to end.
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Strong Python skills and experience with Django, APIs, React, and TypeScript.
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Hands-on experience with agent systems, including planning, tool calling, structured outputs, context and state management, retries, and orchestration.
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Experience building external API and business software integrations.
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Ability to turn loosely defined user needs into clear product capabilities and reusable system abstractions.
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Experience debugging across prompts, model outputs, application code, databases, and APIs, and using production signals to guide improvements.
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Background in LLMs, model evaluation, or prompt engineering in production is valuable, as is experience optimizing distributed systems for latency, cost, and reliability.
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A degree from a strong engineering program, plus startup experience or a demonstrated record of career progression.
Compensation & Benefits
Visa sponsorship is not available.
Location
On-site in Palo Alto, United States.