The Enterprise Network Operations and SRE team is looking to add a seasoned Technical SRE lead to help actualize the SRE vision for our network infrastructure. We are looking for an engineer who is passionate about the network and making its operation seamless with a focus on user experience. This role will offer several opportunities to solve problems by being hands-on with troubleshooting, focused on network automation, observability, documentation, and excellence in operations.
This Network SRE will be dedicated to enhancing network operations, diligently working to minimize manual labor and achieve Service Level Objectives (SLOs) amongst many goals. Our approach includes minimizing reactive operational tasks, documenting KB articles that can be used by Bots, following through on RCAs, conducting blameless postmortems, and proactively identifying and mitigating network risks to foster continuous improvement. This crucial role will be focused on user satisfaction and brilliance in Network Operations. This SRE engineer will focus on tackling significant projects and is committed to fostering a supportive atmosphere that offers the mentorship necessary for professional development and growth. They will bring a wealth of skills and experience to be a sought after mentor, who leads by example.
What you'll be doing:
Owning the operational aspect of the network infrastructure, ensuring its high availability and reliability.
Partnering with architecture and deployment teams to guarantee that new implementations are supportable and align with production standards.
Advocating for and implementing automation to reduce toil and enhance operational efficiency.
Monitoring network performance, identifying areas for improvement, and coordinating with relevant teams to execute enhancements.
Collaborating with SMEs to resolve production issues swiftly and effectively, maintaining customer satisfaction.
Identifying opportunities for operational improvements and partnering with teams to develop solutions that drive excellence and sustainability in network operations.
What we need to see:
BS degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.
Professional Experience: Minimum of 10 years of industry experience in network site reliability engineering, network automation, network operations, or related areas. Experience on both campus and data center networks.
Monitoring Tools: Familiarity with network management tools such as Prometheus, Grafana, Alert Manager, Nautobot/Netbox, BigPanda
Network Automation: Expertise in automating networks using frameworks such as Salt, Ansible, or similar.
Programming and Scripting Skills: In depth experience in one or more of the following: Python, Go. Capable of going beyond simple scripts to build systems that monitor and manage a network.
Network Skills: Knowledge in network technologies such as TCP/UDP, IPv4/IPv6, Wireless, BGP, VPN, L2 switching, , Firewalls, Load Balancers, EVPN, VxLAN, Segment Routing. Subject matter expertise in at least one of these domains. Proven track record in network operations.
Service Tooling: Skills with ServiceNow and Jira
System Administration: Knowledge of Linux system fundamentals.
Problem-Solving and Communication: Systematic problem-solving approach, critical thinking, coupled with excellent communication skills and a strong sense of ownership and drive.
Ways to stand out from the crowd:
Support Automation: Track record of taking operational signals through means such as SNMP, Syslog, Streaming Telemetry to solve operational challenges
Code Optimization: History of debugging and optimizing code; automating routine tasks.
Platform Exposure: Experience with Mellanox/Cumulus Linux, Palo Alto firewalls, Netscalers and F5 load balancers
Network Technologies: In-depth EVPN experience at scale
Previous SRE experience
Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
