Agent Engineer
At Clera · Palo Alto; Palo Alto, California, United States
- Engineering
- Full-time
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- Posted
- 16 October 2026
- First seen by us
- 17 October 2026
- Last checked
- 10 hours ago
Job description
From Clera’s job post, as they wrote it.
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
* Explore advances in agent technology and identify opportunities to solve user problems.
* Translate model capabilities into reliable, reusable skills and workflows.
Read the full description
* Build and evolve Python agent systems, including orchestration, context management, retries, and error recovery.
* Design integrations with email, calendars, messaging, browsers, documents, CRMs, and other business software.
* Own capabilities across Python services, Django, APIs, React interfaces, data models, background jobs, and production operations.
* Create platform abstractions that make capabilities easier to compose, extend, and maintain.
* Improve latency, cost, reliability, and safety in high-volume agent execution.
* Use evaluations, production traces, and user feedback to find and fix quality issues.
* Set technical direction for ambiguous problems and contribute to design reviews.
What We're Looking For
* At least 5 years of experience building and operating production software systems end to end.
* Strong Python skills and experience with Django, APIs, React, and TypeScript.
* Hands-on experience with agent systems, including planning, tool calling, structured outputs, context and state management, retries, and orchestration.
* Experience building external API and business software integrations.
* Ability to turn loosely defined user needs into clear product capabilities and reusable system abstractions.
* Experience debugging across prompts, model outputs, application code, databases, and APIs, and using production signals to guide improvements.
* Background in LLMs, model evaluation, or prompt engineering in production is valuable, as is experience optimizing distributed systems for latency, cost, and reliability.
* 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.
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