Tech Lead Manager, Product Growth
$250k - $300k • Remote • Mountain View, CA
Posted 11h ago
Job Location
Mountain View, CA
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Engineer
About the job
Glean is seeking a product-minded, hands-on, and technically strong Tech Lead Manager to establish and lead its Product Growth engineering function. This role offers the chance to shape a new growth engineering capability at a critical time for Glean as it expands the reach and impact of its Work AI platform. You will operate at the intersection of product engineering, data, experimentation, and applied AI to drive user discovery, adoption, and engagement with Glean.
The Product Growth team is responsible for the complete user journey, from initial discovery and quick value realization to habit formation and expanded product usage. This encompasses the entire lifecycle from invitation and first sign-in through activation, onboarding, engagement, re-entry, and broader adoption across teams and functions. The team focuses on key entry points and touchpoints, including login and setup flows, the home page, navigation, desktop and browser experiences, in-product education, lifecycle communications, and product-led expansion, all aimed at making Glean more discoverable, understandable, and regularly used.
Responsibilities
- 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.
- Utilize 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.
