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GL
Senior Technical Program Manager (Infrastructure)
Glean · San Francisco, United States
About The Role
Join Glean, a company at the forefront of Work AI technology. As a Senior Technical Program Manager (Infrastructure), you will lead large-scale, cross-functional initiatives that define, scale, and optimize our infrastructure platform. You will work closely with various teams to design orchestration systems, streamline deployments, and build the foundations that power our search and AI capabilities. This role requires a strong understanding of cloud infrastructure, a builder mindset focused on automation and efficiency, and extensive experience in technical program management or infrastructure.
- Lead large-scale, cross-functional initiatives to define, scale, and optimize the infrastructure platform.
- Drive the company’s Infrastructure roadmap across Setup & Deployment, Runtime, Storage, and AI Infra.
- Coordinate cross-team delivery of high-impact programs such as data pipeline scalability, LLM infrastructure expansion, or infra observability improvements.
- Ability to structure complex multi-quarter infrastructure programs with clear milestones and measurable impact
- Strong understanding of cloud infrastructure (AWS, GCP, or Azure) including compute, networking, storage, and orchestration systems
- Builder mindset with focus on automation, reliability, and efficiency
- 8-10+ years of experience in technical program management, infrastructure, or SRE, with at least 3-5 years managing infra or platform-scale programs
- BS/MS in Computer Science, Engineering, or a related technical field
- Proven success delivering cross-functional infrastructure programs in B2B or enterprise environments where scalability, uptime, and performance are critical
- Experience working closely with Infra, SRE, and ML/AI teams on distributed systems or data infrastructure
- Strong written and verbal communication and ability to manage through ambiguity, anticipate scaling challenges, and align teams across priorities
- Understanding of data pipelines, ML training workflows, and LLM runtime infrastructure is a plus
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