Staff Technical Program Manager

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.We're looking for a Staff Technical Program Manager to drive the strategy, planning, and execution of large-scale, cross-functional programs across Talent Enterprise Engineering and other org partners. In this role, you'll lead cross-functional 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.Responsibilities:Lead and drive end-to-end delivery of multiple concurrent, high-complexity AI-driven engineering programs across Talent Enterprise Engineering and LinkedIn — from scoping and roadmap planning through launch and post-launch measurement.Champion AI-native program management by using AI/LLM-based tools — for status synthesis, risk detection, meeting summarization, and roadmap drafting — to run leaner, faster program operations, and model this behavior for other TPMs in the org.Partner with engineering on AI system design trade-offs — model selection, latency/cost/accuracy balance, data pipelines, and evaluation frameworks — and translate those decisions into program risk and timeline impact.Own AI-specific program rigor, including responsible-AI review checkpoints, model evaluation and testing cycles, and compliance/privacy review gates that fall outside standard software launch checklists.Own the delivery of large, highly cross-functional programs by developing detailed plans with clear milestones and goals, leveraging technical depth to identify and mitigate risks, resolve dependencies, remove impediments, and ensure timely, smooth launches.Partner with engineering leads, architects, and product leaders to identify technical dependencies, risks, and critical path, and drive resolution across teams.Define and own program operating rhythms: planning cadences, milestone tracking, cross-team sync structures, and executive report...