Sr. Software Engineer - Enterprise Infrastructure
Productivity Engineering is a team at LinkedIn that builds products that power LinkedIn’s business. We drive technology vision, architecture, and design systems that help the company deliver on major business processes (go-to-market, sales, finance, and customer support, etc.). We deliver applications and products that let our customers do business with us in a seamless way, help grow our top line, and increase our efficiency.
This role focuses on building and maintaining scalable, reliable, and secure infrastructure that empowers every developer at LinkedIn. You will manage and scale large-scale enterprise infrastructure across 5 data centers, 11 regional offices and cloud environments like Azure, while driving automation to reduce operational toil and improve developer productivity. Your work will involve managing distributed systems, including orchestration (e.g., Kubernetes), compute, storage, and networking, while ensuring platform reliability, security, compliance, and observability.
At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.
Responsibilities:
Design and build platform services and infrastructure automation tools to support large-scale deployments
Collaborate on technical strategy and roadmap to improve infrastructure scalability, performance, and reliability
Implement Infrastructure-as-Code (IaC) and CI/CD best practices to improve deployment efficiency and consistency
Diagnose and resolve complex system-level and production issues across services and multiple layers of the technology stack
Collaborate with cross-functional teams (e.g., AI, data infrastructure, product) to build scalable and reliable platform solutions
Develop and maintain distributed systems supporting compute, storage, networking, and cloud infrastructure
Establish and track success metrics for projects and products to measure system reliability and performance
Basic Qualifications:
BS/BA degree in Computer Science, Engineering, or related technical field, or equivalent practical experience
4+ years of experience in software development, infrastructure engineering, or distributed systems
3+ years of programming experience in object-oriented or functional languages such as Java, Python, Go, C++, or Scala
Experience working with cloud platforms (e.g., Azure, AWS, or GCP), containerization (e.g., Kubernetes), and distributed systems
Experience with monitoring, observability, and infrastructure automation tools and practices
Preferred Qualifications:
MS or PhD in Computer Science or related technical discipline
5+ years of experience designing and developing highly available and scalable web or infrastructure applications
Experience working with production-grade distributed systems and end-to-end monitoring and observability platforms
Experience with object-oriented design, coding, and testing patterns using languages such as Java, C++, or similar
Experience improving performance, availability, and reliability of large-scale systems
Experience with infrastructure domains such as networking, compute, storage, or databases
Understanding of performance patterns and common failure modes in distributed systems
Experience contributing to technical strategy and roadmap planning for infrastructure or platform systems
Experience collaborating with stakeholders across engineering and product teams
Experience mentoring engineers to improve technical execution and career development
Suggested Skills:
Distributed Systems and Infrastructure Engineering
Cloud Platforms and Containerization (e.g., Azure, Kubernetes)
Infrastructure Automation and CI/CD
Observability and System Reliability Engineering
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