Sr. Software Engineer - Network Infrastructure Observability

Sr. Staff Software Engineer - Network Infrastructure Observability

• Full-time
• Workplace Type:
  Hybrid

Linked In 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 Linked In, 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 Linked In office on select days, as determined by the business needs of the team.

This role will be based in Mountain View, CA.

The Network Infrastructure Observability team is responsible for delivering the platforms, tools, and insights that ensure our global network operates with high reliability, performance, and efficiency. We build large-scale data pipelines, real-time monitoring systems, and intelligent analytics that empower engineering and operations teams to detect anomalies, predict failures, and optimize network behavior. Our work directly impacts availability, capacity planning, and service health across all data center and backbone network environments.

As a Senior Staff Software Engineer, you will serve as a technical leader driving the architecture, innovation, and execution of next-generation observability systems for our network infrastructure. You will define long-term technical direction, lead cross-org initiatives, mentor senior engineers, and drive solutions for complex distributed systems challenges at massive scale. This role requires deep expertise in backend systems, data processing, and large-scale system design, with strong understanding of networking concepts.

• Lead the architectural design and implementation of large-scale observability platforms, including telemetry ingestion, real-time analytics, network health monitoring, and anomaly detection.
• Drive long-term strategy and roadmaps for network observability, ensuring alignment across infrastructure and network engineering teams.
• Build and optimize data pipelines and streaming platforms capable of handling high-volume telemetry from data centers, backbone, and edge networks.
• Partner with network domain experts to define meaningful SLIs/SLOs, improve network resiliency, and drive proactive detection of failures.
• Develop automation, self-healing workflows, and intelligent alerting mechanisms to reduce operational toil and increase network reliability.
• Collaborate with cross-functional engineering groups to ensure system interoperability, standardization, and seamless data exchange across infrastructure layers.
• Mentor and guide engineers across teams, setting best practices for system design, code quality, and operational excellence.
• Influence organizational strategy through technical leadership, design reviews, and cross-group technical forums.
• Drive adoption of modern technologies and architectural patterns to improve latency, scalability, and observability coverage.

• BA/BS Degree in Computer Science or related technical discipline, or equivalent practical experience
• 10+ years of experience building and operating large-scale distributed systems or data-intensive backend platforms.
• Experience with programming languages such as Go, Java, Python, C++, or similar.
• Experience with streaming systems (Kafka, Flink, Spark Streaming, or similar) and high-throughput data pipeline architectures.
• Experience with networking fundamentals: routing, switching, TCP/IP, network telemetry, SNMP, flow data, or similar.
• Proven ability to lead complex technical initiatives end-to-end in a multi-team environment.
• Background in system design skills with focus on scalability, reliability, and performance.
• Experience with container…