$ cat jobs/principal-staff-software-engineer-physical-infrastructure-linkedin3-ece3d0145f8b.json
Principal Staff Software Engineer, Physical Infrastructure
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 are seeking a Principal Staff Software Engineer to join LinkedIn’s Physical Infrastructure organization. As the technical partner to the organizational leader, you will play a critical role in defining the architecture and technical strategy for the software platforms responsible for planning, building, allocating, and managing LinkedIn’s global physical infrastructure. The Physical Infrastructure organization builds and operates the systems that translate business and product demand into deployed infrastructure capacity. These platforms support the end-to-end lifecycle of data center capacity, including long-range planning, demand forecasting, site and space planning, hardware procurement, supply-chain coordination, infrastructure construction, hardware allocation, deployment, and lifecycle management. As our infrastructure consumers and their solutions evolve, this role will also define and manage the contracts between the Physical Infrastructure platform and its customers. You will ensure that platform APIs, data models, workflows, capacity commitments, and service-level expectations remain clear