Sr. Staff Software Engineer Network Infrastructure Observability

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.

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.

Responsibilities:

• 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.

Qualifications :

Basic Qualifications:

• 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 platforms (Kubernetes) and microservices.

Preferred Qualifications:

• Experience working in hyperscale or large distributed cloud environments.
• Background in building observability stacks (metrics logs traces) or network monitoring platforms.
• Familiarity with machine learning for anomaly detection or predictive analytics.
• Experience with infrastructure automation or configuration management tools.
• Experience with influencing across organizations (tech lead architect principal/IC leadership roles).

Suggested Skills:

• Distributed Systems
• Observability
• Monitoring Systems
• Technical Leadership

You will Benefit from our Culture

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. LinkedIn is committed to fair and equitable compensation practices.

The pay range for this role is $181000 to $297000. 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 Information :

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No

Employment Type :

Full-time