Sr. Software Engineer - Enterprise Infrastructure
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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
Requirements
- 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
- 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
- India Disability Policy
- LinkedIn is an equal employment opportunity employer offering opportunities to all job seekers, including individuals with disabilities. For more information on our equal opportunity policy, please visit https://legal.linkedin.com/content/dam/legal/Policy_India_EqualOppPWD_9-12-2023.pdf
- Global Data Privacy Notice and Compliance Posters for Job Candidates
Benefits
Additional Information
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.
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