обновлено 5 дней назад
Senior Technical Program Manager, Infrastructure (AI)
198 000 - 235 500$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Technical Program Manager, Infrastructure (AI): Leading large-scale infrastructure programs across deployment, runtime, storage, reliability, cost efficiency, and AI systems with an accent on orchestration, observability, and scalable platform foundations. Focus on coordinating infrastructure migrations, ML pipelines, LLM serving expansion, disaster recovery, and performance optimization across engineering teams.
Location: Hybrid, four days per week in the Mountain View, California office
Salary: $198,000–$235,500 annual base salary
Company
Glean provides a Work AI platform with enterprise search, AI assistants, AI agents, SaaS connectors, flexible LLM support, and APIs on a secure, extensible platform.
What you will do
- Lead end-to-end infrastructure programs spanning compute, networking, storage, orchestration, and AI workloads.
- Drive the infrastructure roadmap across setup and deployment, runtime, storage, and AI infrastructure.
- Define standards for environment provisioning, deployment automation, configuration governance, runtime health, scaling, and disaster recovery.
- Coordinate data pipeline scalability, LLM infrastructure expansion, infrastructure migrations, capacity planning, and observability initiatives.
- Establish metrics for reliability, performance, and cost efficiency and improve visibility into infrastructure cost drivers.
- Communicate program status, risks, milestones, and measurable impact to engineering leadership and stakeholders.
Requirements
- Bachelor’s or master’s degree in Computer Science, Engineering, or a related technical field.
- 8–10+ years of experience in technical program management, infrastructure, or SRE, including 3–5 years managing infrastructure or platform-scale programs.
- Experience delivering cross-functional infrastructure programs in B2B or enterprise environments where scalability, uptime, and performance are critical.
- Experience working with Infrastructure, SRE, and ML/AI teams on distributed systems or data infrastructure.
- Strong understanding of cloud infrastructure, including compute, networking, storage, and orchestration systems across AWS, GCP, or Azure.
- Ability to structure complex multi-quarter programs, manage ambiguity, anticipate scaling challenges, and align teams across priorities.
Nice to have
- Understanding of data pipelines, ML training workflows, and LLM runtime infrastructure.
Culture & Benefits
- Medical, vision, and dental coverage.
- Paid time off and a 401(k) contribution option.
- Home office improvement, education, and wellness stipends.
- Regular company events and daily healthy lunches.
- Inclusive workplace with a focus on diverse backgrounds and perspectives.
Hiring process
- Complete a brief AI-focused exercise or discussion as part of the interview process.
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