Distinguished Software Engineer, Systems Infrastructure - Compute, Deployment, Infrastructure a[

Distinguished Software Engineer, Systems Infrastructure - Compute, Deployment, Infrastructure as Code (IaC)

• Full-time
• Workplace Type:
  Hybrid

This role will be based in Mountain View, CA OR Bellevue, WA.

We are seeking a Distinguished Engineer to help shape the future of Linked In’s Core Infrastructure platform, which provides shared system services within a large-scale, private, on-premise distributed environment.

This role will focus on building technical strategy and raising the bar across multiple infrastructure domains, with particular emphasis on Compute Infrastructure, Deployment, and Infrastructure as Code (IaC).

The work location of this role is hybrid, meaning it will be performed both from home and from a Linked In office on select days, as determined by the business needs of the team.

• You will partner directly with senior engineering leaders to define long-term technical strategy across Linked In’s core infrastructure, including compute, deployment, and Infrastructure as Code
• Lead cross-team and cross-functional initiatives
• You will head cross team/cross functional discussions and drive alignment on technology strategy.
• You will contribute directly to initiatives through a combination of design and implementation activities.
• You will actively improve the level of craftsmanship at Linked In by developing best practices and defining best strategies.
• You will define the bar for quality and efficiency of software systems while balancing business impact, operational impact and cost benefits of design and architectural choices.
• Influence and mentor engineers across the organization, raising the bar for systems thinking and technical depth
• Drive alignment across organizations on multi-domain infrastructure architecture, balancing scalability, reliability, and cost
• Help evolve Linked In’s private cloud and fleet infrastructure strategy, enabling efficient operation at massive scale
• Foster a culture that values diverse perspectives while navigating complex, ambiguous technical decisions

• Bachelor's degree in Computer Science or a related field, or equivalent experience
• 10+ years of relevant work experience in infrastructure engineering
• Experience leading technical projects with multiple stakeholders

• PhD in a relevant field or related discipline (machine learning, statistics, computer science etc.), or equivalent research experience
• 15+ years experience in building large-scale, mission-critical infrastructure and distributed systems, with at least 5 of those years in a technical leadership position
• Deep expertise in at least one of the following domains, with working experience across others:
  Deployment
• Deep expertise in at least one of the following domains, with working experience across others:
  Infrastructure as Code
• Experience with messaging and streaming systems (e.g., Kafka, pub/sub architectures, event‑driven systems)
• Proven ability to operate across infrastructure domains, contributing to areas such as fleet management, control planes, and private cloud systems
• Experience designing and evolving high‑scale, on‑premise or hybrid cloud infrastructure
• Strong systems‑level thinking, with the ability to move between domains (e.g., networking - storage - distributed systems)
• Proven track record of leading cross‑company, high‑impact infrastructure initiatives from concept through production at scale
• Experience mentoring senior engineers and influencing technical direction across large organizations
• Experience leading high‑impact, cross‑company initiatives

• Infrastructure
• Distributed Systems
• Deployment
• Infra-as-code

We strongly believe in the well-being of our employees and their families. That is why we offer generous health and wellness programs and time away for employees of all levels.

Linked In is committed to fair and equitable compensation practices. The pay range for this role is $253,000 to $416,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be…