Tech Lead Manager, Product Growth
- Salary
- $250,000 - $300,000 annually
- Level
- Lead
- Work type
- Hybrid · Mountain View
Not stated in the posting: visa.
Open. First seen 31 October 2026.
About the role
About Glean:
Glean's standard text
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:
We're hiring a product minded, hands on, technically strong Tech Lead Manager to help establish and lead our Product Growth engineering function. This is an opportunity to shape a new growth engineering capability at a pivotal moment for Glean as we expand the reach and impact of our Work AI platform. You will work at the intersection of product engineering, data, experimentation, and applied AI to help more people discover, adopt, and continuously engage with Glean.
This is a high impact, full stack leadership role for a software engineering leader who can guide architecture, partner deeply with product, design and data science, and grow a strategically important team.
The Product Growth team owns the end-to-end experiences that help users discover Glean, get to value quickly, build lasting habits, and expand their use of the product. This includes the journey from invitation and first sign-in through activation, onboarding, engagement, re-entry, and broader adoption across teams and functions. The team works across key entry points and touch points—including login and setup flows, the home page, navigation, desktop and browser experiences, in-product education, lifecycle communications, and product-led expansion—to make Glean easier to discover, understand, and use regularly.
You will:
- Define technical direction and lead execution for product growth initiatives across Glean’s user-facing experiences.
- Partner with Product, Design, Data Science, Marketing, and Applied AI to identify and prioritize opportunities that increase product awareness, adoption, activation, and engagement.
- Lead a team of full-stack engineers in building thoughtful, measurable experiences that help users realize value from Glean more quickly and return to the product more frequently.
- Use product data, customer insights, behavioral analysis, and experimentation to understand growth opportunities and make informed technical and product decisions.
- Help establish a strong experimentation and measurement foundation, including clear hypotheses, success metrics, instrumentation, experiment design, analysis, and iteration.
- Own projects end to end, from identifying a user or customer problem through technical design, implementation, launch, measurement, and follow-through.
- Stay close to the code and architecture, contributing directly where needed, reviewing designs and code, debugging complex issues, and maintaining a high technical bar.
- Bring strong backend and systems leadership to the team while partnering effectively across the full stack and user-facing product experience.
- Collaborate with engineering teams across Glean to deliver cohesive experiences and build scalable foundations for growth.
- engage with users and customers when useful to understand their needs, identify friction, and ensure that growth initiatives solve meaningful problems
- As the team grows, hire, coach, and develop engineers; establish effective engineering practices; and create an environment of ownership, learning, and high-quality execution.
About you:
- 8+ years of software engineering experience building production distributed systems or cloud‑native applications.
- 1+ years of engineering management experience of a full stack team
- BS/BA in Computer Science or related field, or equivalent practical experience.
- You are a product-forward software engineering leader with experience building and shipping user-facing products, preferably in B2B SaaS, AI, productivity, collaboration, or other high-engagement software.
- You have a strong track record of execution and can lead a group of engineers through ambiguity, make sound technical decisions, and deliver meaningful outcomes.
- You have partnered effectively with Product Managers, Designers, and Data Scientists to define problems, evaluate tradeoffs, and deliver measurable product improvements.
- You are highly analytical and comfortable using data to understand user behavior, evaluate opportunities, define success metrics, and assess experiment results.
- You have demonstrated experience with product growth, experimentation, activation, adoption, engagement, retention, or other data-driven product optimization work.
- You have a strong understanding of customer needs and enjoy building products that users discover, adopt, and use regularly.
- Experience building or working with agentic AI products, large language model applications, machine learning systems, or AI-assisted product experiences is a plus.
Location:
- This role is hybrid (4 days a week in our Mountain View office)
Compensation & Benefits:
The standard base salary range for this position is $250,000 - 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’re committed to building and sustaining a diverse, inclusive workplace. We strive to attract and retain people with a wide range of backgrounds, experiences, and perspectives, and we do not discriminate on the basis of 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.
Glean's standard text
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.
Glean's standard text
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.
What this role asks for
Particular to this role
Machine Learning
Rare in Glean's other 79 open postings.
In most of Glean's ads
GitHub · LLM · ServiceNow
Named in most of its open postings, whatever the role.
79% of this description is written for the role. The rest is Glean's standard text, folded away below.
Compared with Glean's other open jobs.
The team: Engineering HIRES STEADILY
This role is one of 30 open in Engineering. 13 were posted in the last 30 days and the oldest in April: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
GitHub (30 of 30), LLM (30 of 30), ServiceNow (30 of 30), Golang (20 of 30), Java (19 of 30), Python (17 of 30), C++ (12 of 30)
OTHER ROLES ON THIS TEAM
- Design Engineer posted Oct 27
- Senior Site Reliability Engineer posted Oct 23
- Software Engineer, Native Mobile posted Oct 23
- AI Engineer - Quality and Post-Training posted Oct 23
- Software Engineer posted Oct 23
- Software Engineer posted Oct 23
- Software Engineer posted Oct 23
- AI Engineer - Data and Evals posted Oct 23
- Machine Learning Engineer, Enterprise Brain posted Oct 16
- Software Engineer, Agentic Runtime posted Oct 12
- Tech Lead Manager, AI Evaluations posted Oct 12
- Software Engineer, Tech Lead, Admin Console posted Oct 6
- Platform Security Engineer posted Aug 27
- Application Security Engineer posted Aug 27
- Machine Learning Engineer, Assistant Quality posted Aug 3
- Software Engineer, Cloud Infrastructure posted Jun 30
- Software Engineer, APIs & Context Platform posted May 19
- Software Engineer, Consumption Billing & Revenue Platform posted Feb 3
- Software Engineer, Data Foundations posted Dec 8
- Software Engineer, Developer Productivity posted Oct 2
- Supply Chain Security Engineer posted Sep 26
- Software Engineer, Storage posted Sep 18
- Software Engineer, AI & Security posted Sep 4
- Software Engineer, AI/ML Infrastructure posted Nov 26
- Software Engineer, Product Backend posted Jun 4
- Software Engineer, Machine Learning posted Jun 29
- Software Engineer, Frontend posted Apr 8
- Software Engineer, Fullstack posted Apr 8
- Software Engineer, Backend posted Apr 8
From the team and dates on Glean's own job board.
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