Staff Technical Program Manager

LinkedInMountain View, CA
$139,000 - $229,000Hybrid

About The Position

LinkedIn is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works. At LinkedIn, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a LinkedIn office on select days, as determined by the business needs of the team. This role will be based in Mountain View, CA. LinkedIn's Talent Marketplace Engineering org builds the systems and platforms that connect hundreds of millions of members with jobs, skills, and career opportunities. Our work spans online jobs, job recommendations, AI-powered matching, applicant experience, and the platforms that power LinkedIn's core economic value — helping people find the right opportunity at the right time. We're looking for a Staff Technical Program Manager to drive the strategy, planning, and execution of large-scale, cross-functional programs across Talent Marketplace Engineering and other infra org partners. In this role, you'll lead AI and LLM based projects, and partner closely with engineering, product, data science, and design to deliver high-impact initiatives that shape how LinkedIn members and enterprise customers experience career mobility. At the Staff level, you are expected to independently own ambiguous, complex programs, influence technical and product direction, and raise the bar for program management practices across the org.

Requirements

  • Bachelor’s degree in Engineering, Computer Science, Software Management or related technical field, or equivalent practical experience.
  • 5+ years of technical program management or equivalent experience in a software engineering organization.
  • Experience in leading AI-driven products in the industry.

Nice To Haves

  • Master’s degree in Engineering, Computer Science, Software Management or related technical field.
  • Experience in consumer-facing or marketplace products, ideally in search, recommendations, or marketplace matching systems.
  • Familiarity with AI/ML product development lifecycles (model training pipelines, offline/online experimentation, responsible AI practices).
  • Experience leading programs that span multiple teams and quarters with organizational dependencies.
  • Background with capacity management and planning (GPU, TPU, etc).
  • Proven track record of delivering large, cross-functional programs involving multiple engineering teams in a fast-paced environment.
  • Solid understanding of system foundations and AI modeling lifecycle.
  • Excellent written and verbal communication.
  • Demonstrated ability to operate independently in ambiguous environments and drive clarity.

Responsibilities

  • Lead and drive end-to-end program delivery for multiple concurrent, high-complexity AI-driven engineering initiatives across Talent Marketplace Engineering and LinkedIn, from scoping and roadmap planning through launch and post-launch measurement.
  • Partner with engineering leads and architects to identify technical dependencies, risks, and critical path; drive resolution across teams.
  • Define and own program operating rhythms and process: planning cadences, milestone tracking, cross-team sync structures, and executive reporting.
  • Drive alignment across orgs and business stakeholders on scope, timelines, and trade-offs.
  • Anticipate and proactively mitigate risks; escalate blockers with clear recommendations.
  • Contribute to org-level planning processes (half-yearly roadmap, OKR setting) by synthesizing engineering capacity and business priorities.
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