> Markdown version of [/jobs/ext/4356566-staff-software-engineer-agent-quality](https://www.wearedevelopers.com/jobs/ext/4356566-staff-software-engineer-agent-quality). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Software Engineer, Agent Quality

- **Company:** Databricks
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $200,000.0 - $265,000.0
- **Contract:** Permanent contract
- **Skills:** Continuous Integration, Distributed Systems, Iterative and Incremental Development, Python (Programming Language), Software Construction, Datadog, Large Language Models, Agentic-AI, Data Pipelines, Databricks
- **Published:** October 31, 2026
- **Apply:** https://www.adzuna.com/details/5940315890

## About the Role

* 6+ years industry experience building software systems
 * Strong Python programming skills, with experience building production or research infrastructure
 * Experience building or operating distributed systems, data pipelines, or large-scale infrastructure with a focus on reliability, correctness, and operational maturity
 * Ability to design pragmatic but rigorous systems that produce trustworthy, reproducible signals for complex applications
 * Comfort working across ambiguous research and product boundaries, and partnering with both researchers and engineers to turn ideas into robust internal platforms
 * A high bar for technical quality, strong ownership, and the ability to influence roadmap and execution across multiple teams

Nice to have

 * Experience with devtools, CI/CD platforms, testing frameworks, observability tooling, or benchmarking infrastructure
 * Familiarity with how LLM or agent quality is measured - whether through evals, experimentation platforms, or production monitoring

Pay Range Transparency

## Description

As a Staff Software Engineer - Agent Quality, you will be a founding member of a new team focused on evaluating and continuously improving Databricks' AI Agents. You will design and scale the infrastructure, tooling, and developer workflows that let researchers and engineers evaluate agents rigorously - driving a flywheel where evaluation results feed directly back into agent improvement across the full lifecycle, from development and training to production.
The impact you will have

 * Stand up the foundational evaluation infrastructure for Genie Agents, enabling rigorous benchmarking, regression detection, and quality measurement across research and product teams.
 * Build the flywheel that connects evaluation results back into agent improvement - closing the loop between production signals, training, and iterative development.
 * Shape the long-term technical direction for agent quality infrastructure, with real influence over how Databricks measures and improves its first-party agents and agent development platform.
 * Help shape the long-term technical direction for agent quality infrastructure as Databricks expands its first-party agents and agent development platform.