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Glean Work

Product Manager, AI

Glean Work is hiring a Product Manager, AI in Mountain View, United States. It pays $200k-$300k a year and Level rates it ; you can apply on Glean Work.

Level's read on this job

  • On Level's scale, this AI product manager role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The listed pay starts 12% above the typical AI product manager posting on Level.
  • Tools and skills the posting cites include AI agents and AI evaluation.
  • Level classifies it as a mid-level role.
  • Level lists 119 other open roles at Glean Work.

AI in this role

ai-agentsai-evaluation
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:

As a Product Manager on Glean's AI team, you will own the core systems that make our AI reliable, efficient, and measurably better over time. We're looking for deep skills and hands-on experience in one or both of the following areas:

  • Agent harness: experience designing or shipping the execution layer around the model, including planning, tool calling, context management, sub-agents, skills, memory, and long-running tasks, and making the tradeoffs across intelligence, latency, and cost that determine how well agents perform.
  • Evaluation: experience building the evalsets, benchmarks, judges, and labeled data that gate launches, compare models and harness changes, and drive continuous hill-climbing on quality.

This is a highly technical, cross-functional IC role. You will work closely with AI engineering, data science, and platform marketing teams, and you will partner with leading model providers and help go-to-market teams turn quality improvements into customer proof points.

You will:

  • Set the product strategy and roadmap for your area, grounded in customer workflows, trace data, and eval results.
  • Define what "good" looks like for agentic work, including correctness, helpfulness, formatting, efficiency, and reliability, and turn it into clear, measurable launch bars.
  • Make evidence-based tradeoffs across models, prompts, tools, and harness changes, balancing quality against latency, cost, and capacity.
  • Decide when to use frontier models versus post-training open-weight models for specific tasks, weighing quality, cost, latency, and control, and define the data and evals needed to make post-trained models competitive.
  • Build and scale the operating model for evaluation, including datasets, LLM-as-judge systems, human labeling, and benchmarks.
  • Turn failed runs, poor traces, and user feedback into prioritized product and quality improvements.
  • Partner with model providers and strategic partners on model evaluation, launches, and joint quality work.
  • Give the team context, set direction, and build alignment across engineering, data science, and GTM teams without direct authority.

About you:

  • You have 4+ years of product management experience, ideally on AI/ML, developer-platform, infrastructure, or quality-tooling products serving large enterprises.
  • You have built or worked closely on LLM-powered agents or at-scale AI products, and you understand how harness design choices affect agent behavior.
  • You are fluent in LLM evaluation concepts: evalsets, LLM-as-judge, pairwise/side-by-side judging, judge calibration against human labels, benchmarks, and offline-versus-online alignment.
  • You are comfortable going deep on agentic systems, including multi-turn tasks, tool use, context and memory management, write actions, and tracing and observability.
  • You are rigorous with data and can turn ambiguous quality problems into crisp hypotheses, metrics, and experiments.
  • You have a strong technical background and can engage credibly with engineers and data scientists on system design and experiment results.
  • You are an excellent written and verbal communicator who enjoys engaging with GTM teams and customers, and you can bridge our technical choices with the outcomes our customers care about.
  • You have a proven track record of taking ownership, taking initiative, and delivering results.
  • You have a learning and growth mindset, and you are mission-first.
  • You are an early adopter of AI in your own product craft, and you use coding agents and AI tools to prototype, analyze, and move faster.

Location:

  • This role is hybrid (4 days a week in one of our SF Bay Area offices)

Compensation & Benefits:

The standard base salary range for this position is $200,000 - $300,000 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.

We offer a comprehensive benefits package including competitive compensation, Medical, Vision, and Dental coverage, generous time-off policy, and the opportunity to contribute to your 401k plan to support your long-term goals. When you join, you'll receive a home office improvement stipend, as well as an annual education and wellness stipends to support your growth and wellbeing. We foster a vibrant company culture through regular events, and provide healthy lunches daily to keep you fueled and focused.

We are a diverse bunch of people and we want to continue to attract and retain a diverse range of people into our organization. We're committed to an inclusive and diverse company. We do not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.

#LI-HYBRID

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. Global Data Privacy Notice for Job Candidates and Applicants: Depending on your location, the General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or other privacy laws may regulate the way we manage the data of job applicants. Our full notice outlining how data will be processed as part of the application procedure for applicable locations is available in our Privacy Policy. By submitting your application, you are agreeing to our use and processing of your data as required. US applicants and their applications are subject to arbitration of disputes as outlined in our Applicant Arbitration Agreement.
By clicking “Submit Application,” I confirm that I have read the Global Data Privacy Notice and the Applicant Arbitration Agreement, and I agree to the terms.

How we rate this

Product Manager, AI at Glean Work rates 69 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsAI Evaluation

Also common in AI product manager jobs at this level

Pay

This job starts at
$200k
Typical AI product manager job
$179k

This posting starts 12% above the typical AI product manager job. See AI product manager jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. How do you decide that one model's output is better than another's for a given task?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI agents and AI Evaluation. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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