AI Engineer - Data and Evals

Glean; San Francisco (CA); Hybrid; USD 200,000 - 280,000; Full time

Benefits offered by this job

Medical, Vision, Dental

Generous time-off

401k plan

Home office stipend

Education stipend

Wellness stipend

Healthy lunches

Job summary

Glean, the Work AI platform redefining enterprise search and knowledge work, seeks a seasoned software engineer to build eval and benchmarking systems for LLM-driven products. You will craft datasets, design scalable eval pipelines, and ensure high-quality, measurable results across wide data sets.

Join a hybrid team in the SF Bay Area, work on agentic AI capabilities, observability, and CI/CD integrations, and help ship reliable AI-powered features that accelerate productivity for thousands of

Qualifications

• 5+ years of software engineering experience with Go and/or Python.
• Experience building datasets and benchmarks for LLM use-cases or agents.
• Familiar with CI/CD and observability tooling.

Responsibilities

• Build eval sets and benchmarks from expert-curated examples, production data, synthetic data, and past failures, covering edge cases and key user slices.
• Build and scale the eval platform and agent observability: experiment pipelines, trace capture and replay, and dashboards, with reproducible, affordable runs.
• Build agentic LLM verifiers for correctness, groundedness, citation quality, and task success, calibrating them with human labels using clear rubrics.
• Run evals at every stage, from CI and pre-release suites to production traffic, and report results with confidence intervals.
• Build enterprise simulation environments with simulated users and realistic company data to test multi-step agent tasks.
• Diagnose failures by slice and trace, and turn eval results into concrete fixes, weighing quality against latency and cost.

Skills

Go

Python

APIs

Data modeling

Testing

Distributed pipelines

OpenTelemetry

CI/CD

SQL

Tools

OpenTelemetry

Job description

About Glean

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles.

About Glean

Glean is the Work AI platform that helps everyone work smarter with AI. What began as the industry’s most advanced enterprise search has evolved into a full-scale Work AI ecosystem, powering intelligent Search, an AI Assistant, and scalable AI agents on one secure, open platform. With over 100 enterprise SaaS connectors, flexible LLM choice, and robust APIs, Glean gives organizations the infrastructure to govern, scale, and customize AI across their entire business - without vendor lock-in or costly implementation cycles. At its core, Glean is redefining how enterprises find, use, and act on knowledge. Its Enterprise Graph and Personal Knowledge Graph map the relationships between people, content, and activity, delivering deeply personalized, context-aware responses for every employee. This foundation powers Glean’s agentic capabilities - AI agents that automate real work across teams by accessing the industry’s broadest range of data: enterprise and world, structured and unstructured, historical and real-time. The result: measurable business impact through faster onboarding, hours of productivity gained each week, and smarter, safer decisions at every level. Recognized by Fast Company as one of the World’s Most Innovative Companies (Top 10, 2025), by CNBC’s Disruptor 50, Bloomberg’s AI Startups to Watch (2026), Forbes AI 50, and Gartner’s Tech Innovators in Agentic AI, Glean continues to accelerate its global impact. With customers across 50+ industries and 1,000+ employees in more than 25 countries, we’re helping the world’s largest organizations make every employee AI-fluent, and turning the superintelligent enterprise from concept into reality. If you’re excited to shape how the world works, you’ll help build systems used daily across Microsoft Teams, Zoom, ServiceNow, Zendesk, GitHub, and many more. You'll be deeply embedded where people get things done. You'll ship agentic capabilities on an open, extensible stack, with the craft and care required for enterprise trust, as we bring Work AI to every employee, in every company.

About The Role

The bottleneck in building reliable, useful AI is no longer writing code. It's defining what good looks like and measuring how well our products deliver it. That takes high-quality data and evals that teams can trust.

You Will

• Build evalsets and benchmarks from expert-curated examples, production data, synthetic data, and past failures, covering edge cases and key user slices.
• Build and scale the eval platform and agent observability: experiment pipelines, trace capture and replay, and dashboards, with reproducible, affordable runs.
• Build agentic LLM verifiers for correctness, groundedness, citation quality, and task success, and calibrate them against human labels using clear rubrics.
• Run evals at every stage, from CI and pre-release suites to sampled production traffic, and report results with confidence intervals.
• Build enterprise simulation environments with simulated users and realistic company data to test multi-step agent tasks.
• Diagnose failures by slice and trace, and turn eval results into concrete fixes, weighing quality against latency and cost.

About You

• 5+ years of software engineering experience with strong Go and/or Python and backend fundamentals: APIs, data modeling, testing, and distributed pipelines. TypeScript is a plus.
• Experience building datasets and benchmarks for LLM use-cases, RAG, or agents, including evalset curation and synthetic data generation.
• Familiarity with eval methodologies and their tradeoffs: deterministic metrics, LLM-as-a-judge, pointwise vs pairwise grading, human labeling, and judge calibration.
• Experience building eval or experiment infrastructure that runs reliably at scale, including CI/CD integrations and observability tooling like OpenTelemetry.
• Strong analytical skills: you dig into traces and failure cases, write SQL, and use data and metrics to explain why quality moved.
• Nice to have: experience with simulation environments and/or model post-training techniques.

Location:

• This role is hybrid (4 days a week in our Mountain View or San Francisco office)

Compensation & Benefits

The standard base salary range for this position is $200,000 - $280,000 annually. Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for variable compensation, equity, and benefits.

• Medical, Vision, and Dental coverage
• generous time-off policy
• opportunity to contribute to your 401k plan
• home office improvement stipend
• annual education and wellness stipends
• healthy lunches daily

AI-First Mindset At Glean

At Glean, AI fluency is core to how we work and we’re committed to ensuring every new hire feels confident integrating AI into their everyday work. As part of the interview process, you’ll complete a brief AI-focused exercise or discussion so we can understand how you think about, design, and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today — prior Glean experience isn’t required.