# Tech Lead Manager, AI Evaluations at Glean

- Company: Glean
- What the company does: Glean is the Enterprise AI platform connected to your enterprise's data. Find, create, and automate anything. Explore what Glean can do for you! Backed by General Catalyst, Kleiner Perkins and Lightspeed.
- Company website: https://www.glean.com/
- Type: Startups (AI role)
- Level: Senior
- Location: Mountain View, CA
- Work setup: On-site
- Pay: $250K to $350K base salary per year (USD)
- Posted: 2026-10-12
- Apply by: 2026-11-26
- Apply: https://job-boards.greenhouse.io/gleanwork/jobs/4742957005?utm_source=1752vc&utm_medium=careers
- Page: https://www.1752.vc/careers/jobs/glean-tech-lead-manager-ai-evaluations/

## About the role

The bottleneck in building reliable and useful AI systems isn’t writing code anymore. It’s knowing what good looks like, applying that knowledge and experience from production usage into building rigorous evals, and using those evals to guide continuous product self-improvement loops. Found on 1752vc Careers, the job board for startup and VC roles.

## What they're looking for

- 10+ years of experience in software engineering, ML infrastructure, data systems, or a related technical field. Experience must include building and operating production systems
- 5+ years of engineering or applied AI team management experience, with a track record of technical leadership, developing engineers and scientists, and delivering cross-functional projects
- Understanding of agent evaluation, including tool calling, multi-turn behavior, trajectory quality, task completion, and recovery from errors, experience with safety testing or red teaming is a plus
- Strong coding ability in Python or another production language, with sound engineering fundamentals in testing, APIs, data modeling, and reliable distributed systems
- Experience building scalable data and developer platforms, experiment pipelines, or CI/CD integrations, familiarity with cloud infrastructure, Kubernetes, data stores, and observability is beneficial
- Strong judgment about measurement quality, including dataset representativeness, judge calibration, reproducibility, uncertainty, and the risk of optimizing to a narrow metric

Tags: Engineering

Source: 1752vc Careers, https://www.1752.vc/careers/jobs/glean-tech-lead-manager-ai-evaluations/