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# Staff Software Engineer - Autonomous Verification Platform

- **Company:** Uber
- **Location:** San Francisco, CA, United States (Remote available)
- **Experience:** Expert
- **Salary:** $232,000 - $258,000
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Code Generation, Code Review, Data Structures, Programming Tools, Distributed Systems, Software Engineering, Software Factory, Test Management, Large Language Models, Backend, Agentic-AI, Build Management, Information Technology, Build Tools
- **Published:** October 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d945c43d55e6da7d

## About the Role

* Bachelor's degree in Computer Science or a related field (or equivalent experience).
 * 8+ years of full-time software engineering experience.
 * Strong experience building and operating backend distributed systems.
 * Solid knowledge of algorithms, data structures and system design.
 * Demonstrated ability to set technical direction on ambiguous, high-impact problems.
 * Track record of delivering technical work across teams., * Experience with test infrastructure, CI systems or developer productivity at scale.
 * Familiarity with test quality techniques such as mutation testing, fault injection, contract testing or flaky test management.
 * Experience designing evals or benchmarks for LLM or agent systems, with statistical rigor.
 * Experience applying LLMs or AI agents to developer tooling, code review or test generation.
 * Experience defining a technical vision and bringing teams and leadership along.
 * Experience with large monorepos and build systems such as Bazel. Proficiency in Go or Java.
*

## Description

In this role you will build the systems that decide whether backend changes are safe to land. You will work hands-on to give humans and AI agents a clear signal on which tests are meaningful and trustworthy, and you will help set the team's technical direction. You will be a key contributor to the verification layer of Uber's software factory.

What You'll Do

 * Build systems that measure the quality of backend tests beyond coverage, using techniques such as fault detection, mutation analysis and replay of real historical bugs.
 * Design and build the signals that tell engineers and agents which tests matter for a change, which are reliable, and what a failure means.
 * Build verification for AI-generated code, including independent test generation, behavioral validation and verification artifacts that CI can attest to.
 * Define how we evaluate agents, skills and validators that write or check code, using golden datasets, replay of real bugs and regression tracking across models and prompts.
 * Measure whether our verification signals can be trusted, such as how often judges and validators agree with real outcomes, so humans and agents know when to rely on them.
 * Reduce flakiness and make failures actionable, so engineers and agents know what failed, how to fix it and who to contact.
 * Define and track verification health, such as defect catch rate and flake rate, and catch regressions early.
 * Shape the vision for verification in an agentic world: spec-driven development, independent test generation, and verification evidence that CI can attest to, so human judgment moves from reviewing every PR to defining what correct means.
 * Contribute to the team's technical direction: write design docs, set standards, mentor engineers and partner with CI, build and product teams.