Job Description

This role will be based in Mountain View, CA.

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.

LinkedIn's DC Hardware Automation & Tooling Development team builds the host lifecycle, hardware health, and data center capacity management tools that power Infrastructure Engineering at LinkedIn.
We own tooling for every phase of the hardware lifecycle-from evaluation and qualification, to receiving, building, and allocating hardware for production services. We also build the automation that plans and manages capacity across LinkedIn's data centers, spanning power, space, network, and delivery logistics. Our customers reach across all Infra Engineering-Hardware Capacity, Cloud, Network, Systems, Asset Management, and enterprise DC-Ops/Engineering. The infrastructure we manage is what serves LinkedIn to the world.

As a Staff Software Engineer, you will design and build full-stack systems end to end-from the data models and backend services that drive hardware automation to the web interfaces our internal customers rely on every day. Beyond shipping features, you'll own the reliability, scalability, and operational health of the services you build, applying SRE disciplines to keep our production infrastructure healthy at scale. You will also help set the standard for how our team uses AI to engineer software faster-leveraging the latest agentic coding tools without compromising quality, security, or maintainability.

Responsibilities:

• Design and build scalable, performant, maintainable, distributed systems for managing our production infrastructure.
• Apply SRE disciplines to the systems you own: define and monitor SLOs/SLIs, instrument services for observability (metrics, logging, tracing), reduce toil through automation, and continuously improve reliability, capacity, and performance.
• Build and operate ETL pipelines and data systems that turn raw hardware, capacity, and lifecycle signals into reliable, queryable datasets-and surface them through dashboards and reports that drive operational and planning decisions.
• Participate in on-call rotation, lead incident response, and drive blameless postmortems to systemic resolution.
• Collaborate with our development teams and client stakeholders to define and build systems that meet both user and organizational needs.
• Communicate conceptual ideas, design rationale, and the specifics of a user-centered design process.
• Create and maintain a UX & UI pattern library that is reusable across multiple tools/apps to ensure consistent behaviors for common designs.
• Design backend models and APIs for use by our customers, and support our customers in their use of them.
• Leverage modern AI-assisted development tools (e.g., Claude Code, Codex, and other agentic coding assistants) to accelerate delivery-while upholding correctness, security, and maintainability through testing, code review, and sound engineering judgment.
• Help establish team practices and guardrails for using AI in the development lifecycle in a reliable, high-quality way.
• Provide technical leadership, driving best practices to improve productivity, visibility, and craftsmanship across the organization, as well as among our code-producing customers.

Qualifications

Basic Qualifications:

• BA/BS Degree in Computer Science or related technical discipline
• 5+ years of software development in one or more object-oriented languages such as Java or Python
• 5+ years of hands-on experience with semantic HTML, CSS and object-oriented JavaScript.

Preferred Qualifications:

• 5+ years of relevant work experience
• Experience delivering dynamic applications utilizing modern Front-End frameworks and libraries: React.js and Ant Design.
• Experience in Python development using frameworks like Django and Flask.
• Experience with relational, document-oriented and time series databases such as MySQL and Redis.
• Experience building ETL/data pipelines and workflow orchestration with tools such as Apache Airflow and PySpark.
• Experience with data science and analytics disciplines-data modeling, transformation, and deriving insights from large datasets.
• Experience building dashboards and data visualizations using tools such as Grafana and Power BI.
• Experience with large-scale distributed systems and client-server architectures.
• Experience automating production infrastructure at Internet-scale companies.
• Experience building data center automation or cloud management systems at scale.
• Hands-on experience with SRE practices: observability tooling, SLO/SLI definition, incident management, capacity planning, and reliability engineering.
• Demonstrated, effective use of AI coding tools (Claude Code, Codex, Copilot, or similar) to ship production-quality software-including a clear point of view on where AI accelerates work and how to verify and safeguard its output.
• Ability to diagnose and rectify performance issues at any layer of a multi-tier architecture.
• Experience with Unit / Integration / Visual Testing.

Suggested Skills:

• System Design / Software Architecture / RESTful API Design
• Data Pipelines / Data Engineering
• Technical Leadership / Mentorship
• Data Center Host Lifecycle Management & Capacity Planning
• Data Visualization / Dashboards
• AI-Assisted Development / Agentic Coding

Additional Information

LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $152,000 to $248,000. 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 different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits.