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Glean

AI-powered enterprise search across applications

Tech Lead Manager - Product Growth

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeMountain View, CA, USA

About the Job

Requirements

  • At least 8 years of software engineering experience building production distributed systems or cloud-native applications.
  • At least 1 year of engineering management experience with a full-stack team.
  • A Bachelor of Science or Bachelor of Arts in Computer Science or a related field, or equivalent practical experience.
  • Experience building and shipping user-facing products; experience in B2B SaaS, AI, productivity, collaboration, or other high-engagement software is preferred.
  • A track record of execution, leading engineers through ambiguity, making sound technical decisions, and delivering meaningful outcomes.
  • Experience partnering with Product Managers, Designers, and Data Scientists to define problems, evaluate tradeoffs, and deliver measurable product improvements.
  • Ability to use data to understand user behavior, evaluate opportunities, define success metrics, and assess experiment results.
  • Experience with product growth, experimentation, activation, adoption, engagement, retention, or other data-driven product optimization work.
  • Strong understanding of customer needs and interest in building products that users discover, adopt, and use regularly.

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 building 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 identify growth opportunities and make informed technical and product decisions.
  • Establish an experimentation and measurement foundation, including 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.
  • Contribute directly to code and architecture as needed, review designs and code, debug complex issues, and maintain a high technical bar.
  • Provide backend and systems leadership while partnering 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 as useful to understand their needs, identify friction, and ensure 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.

Desired Qualifications

  • Experience building or working with agentic AI products, large language model applications, machine learning systems, or AI-assisted product experiences.

About the Company

Glean

AI-powered enterprise search across applications

Glean builds an AI-powered search and knowledge assistant that helps employees find information across all of a company's apps and data. Its core product is an enterprise search tool that understands natural language queries and retrieves relevant results from documents, conversations, tickets, and other sources, plus a chat assistant that can summarize and answer questions using that same information. The system uses deep learning language models that adapt to a company's own terminology and context, improving relevance without manual tuning, and it offers hosting options to align with security and data policies. Compared with competitors, Glean focuses on cross-application search, organization-specific language learning, and a combined search-and-chat experience that delivers direct answers and summaries from internal knowledge sources. Its goal is to help teams work faster by turning scattered information into easily accessible answers, reducing time spent searching.

Company size
1,001-5,000
Company stage
Series F
Total funding
$805M
Headquarters
Palo Alto, CA
Founded
2019

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