Product Manager, Agents
Glean Work is hiring a Product Manager, Agents in Bengaluru, India. Level rates it ; you can apply on Glean Work.
Level's read on this job
- Level rates this AI product manager role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting mentions AI agents among its tools and skills.
- Level classes it as a senior role.
- Glean Work has 126 other open roles on Level.
AI in this role
About the Role:
Glean Agents is the platform enterprises use to build, run, and govern AI agents that do real work across departments—including IT, HR, engineering, support, sales, legal, and finance. Agents on Glean already run millions of times a week for customers such as Zillow, Ericsson, and Motive.
The hardest part of an enterprise agent is not the model: it is context and trust—knowing what is true inside a company, who is allowed to see it, and what an agent is allowed to do. Glean’s Enterprise Graph and Personal Knowledge Graph provide permission-aware context across more than 100 enterprise apps, so teams can build on that foundation rather than recreate it.
This is a senior role on a lean, growing product team. You’ll own a meaningful part of the Agents platform, work directly with customers and Glean leadership, and help set direction for your area. Unlike roles focused on a single department, this role spans the enterprise, with product decisions reaching millions of agent runs each week.
You will own one of these problem spaces:
- Building and quality: How business users and engineers create, test, and improve agents, including evaluations, trace debugging, versioning, and regression gates.
- Capabilities: The actions, tools, skills, triggers, and sandboxed execution that let agents read and act in systems such as Salesforce, Jira, ServiceNow, and Workday, as well as open protocols such as MCP and A2A.
- Governance and identity: Agent identity and service credentials, access policies, agent scanning, human approvals, usage and cost controls, and audit capabilities that help enterprises deploy agents in production.
- Channels: Where agents work alongside people—including Slack, Microsoft Teams, email, and Glean Assistant—with support for agents that respond in team channels as well as direct messages.
- Independent agents: AI coworkers that own workflows end to end, act on schedules and triggers, and bring in a person when a decision requires one.
You will:
- Own a problem space end to end—from understanding the customer problem to shipping a capability and driving adoption. You’ll be measured on outcomes, including agents in production and the work they take over, not simply features shipped.
- Co-build with customers. Work alongside IT, legal, or support teams to build agents, find where they break, and turn the learnings into platform capabilities that work across customers.
- Define what good looks like by writing evaluations, reading traces, investigating failures, and deciding when an agent or capability is ready to ship. Shipping is the midpoint, not the finish.
- Design for production from day one, planning for versioning and rollback, observability, least-privilege access, failure handling, approvals, and cost per run.
- Make hard tradeoffs explicit, balancing determinism with reasoning, autonomy with control, and latency with depth. Decide what Glean should build natively and what it should open up through MCP, A2A, and APIs.
- Build with the product every day: use Glean Agents and competing platforms, and prototype agents before writing PRDs.
- Scale what works by partnering with engineering, design, sales, solutions, and partners to take capabilities from a design partner to hundreds of customers.
- Help build the team by shaping how Glean’s growing Agents product and engineering team in Bangalore works.
About you:
- 6+ years of product management experience on technical B2B, platform, or developer-facing products. Equivalent experience as a founder, engineer, or forward-deployed engineer also counts.
- Hands-on experience building agents, including tool use, planning and reasoning loops, memory, multi-agent orchestration, MCP, evaluations, and debugging from traces. Agents built at work, at a startup, or as side projects all count; be ready to discuss what you built and what broke.
- Production instincts: you have shipped systems people depend on and think naturally about reliability, observability, permissions, and cost.
- Fluency with enterprise customers, from the operations lead automating a team’s workflow to the CIO deciding whether agents can act in production.
- Design for production from day one. Plan for versioning and rollback, observability, least-privilege access, failure handling, approvals, and cost per run.
- Make the hard tradeoffs explicit. Weigh determinism against reasoning, autonomy against control, and latency against depth. Decide what Glean builds natively and what it opens up through MCP, A2A, and APIs.
- Build with the product every day. Dogfood Glean Agents and competing platforms, and prototype the agent before you write the PRD.
- Scale what works. Partner with engineering, design, sales, solutions, and partners to take a capability from one design partner to hundreds of customers.
- Help build the team. Glean is growing its Agents product and engineering team in Bangalore, and you will help shape how that team works.
Location:
- This role is hybrid (3 days a week in our Bangalore office)
Compensation & Benefits:
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 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, Agents at Glean Work rates 70 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.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ 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
Also common in AI product manager jobs at this level
Pay
- Typical AI product manager job
- $180k
This posting doesn't list pay. Use the typical AI product manager figure when pay comes up. See AI product manager jobs
Questions you could be asked
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- 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. 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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