Staff Software Engineer - AI Research Infrastructure
Founding member of a new team building foundational evaluation infrastructure and flywheels for Databricks' AI/Genie Agents. Design scalable tooling for benchmarking, regression detection, and quality measurement that drives continuous agent improvement across research, training, and production.
About the job
Impact
- 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.
Requirements
- 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-Haves
- 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
Skills
Python, Distributed Systems, Data Pipelines, Large-Scale Infrastructure, CI/CD, Testing Frameworks, Observability, Benchmarking, Llm Evaluation
Similar jobs
ML Engineering jobs
Talkiatry
United States
Staff-level engineer responsible for building AI agents and automation, evaluating developer AI tools, and driving adoption across the engineering organization. Requires 8+ years of software engineering experience plus production experience with LLMs, agentic systems, and applied machine learning.
Nuro
Mountain View, CA
Develop and productize online mapping models for autonomous navigation using real-world sensor data. The role requires deep ML expertise, robotics or computer vision experience, strong Python and deep learning framework skills, and a staff-level ability to deliver practical solutions.
Nuro
Mountain View, CA
Build and operate ML infrastructure for autonomy teams, including training and deployment pipelines, model observability, inference serving, and compiler platforms across hardware targets. Requires a degree, 3+ years of relevant experience, Python proficiency, and distributed-systems expertise.
Shield AI
San Diego, CA
Develop production C++ perception capabilities for autonomous systems, spanning algorithms, libraries, integration, validation, and release. The role requires deep expertise in at least one perception domain, strong systems debugging, and experience delivering maintainable software in complex robotics or real-time environments.
OnePay
United States
Design and productionize ML, deep learning, and LLM models for personalization, recommendations, and search systems. Requires 7+ years building production ML/AI with business impact and strong cross-functional collaboration skills.