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Lambda is a leader in AI cloud infrastructure serving tens of thousands of customers, from AI researchers to enterprises and hyperscalers. The company's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence.
Lambda is seeking a Senior Director of Network Reliability Engineering to own the health of the company's network end to end. Every customer workload depends on the network, from single-GPU experiments to training runs spanning thousands of GPUs. When infrastructure fails—optics degrade, links flap, switches fail—customers experience stalled jobs, restarts, and lost compute time. This role will lead the organization responsible for operating the existing network flawlessly while reinventing how failures are detected, isolated, and fixed through automation.
You will lead an organization spanning network SRE and automation engineering, incident management, and break-fix coordination with data center teams. Key responsibilities include:
- Own end-to-end network reliability across GPU compute fabrics, data centers, backbone, and edge infrastructure, accountable for availability, time to detect, and time to restore.
- Run break-fix operations at scale: fault detection, triage, hardware replacement, RMA, optics and cabling remediation, and coordination across a growing fleet of data centers.
- Lead networking ops excellence and incident management programs, including on-call rotations, incident command, escalation paths, customer communication, and blameless postmortems that drive engineering fixes.
- Set multi-year strategy for a self-healing network with automated loops that detect, isolate, and repair failures without human intervention.
- Convert manual break-fix work into durable software, measuring toil and tracking the share of failures resolved automatically as a primary outcome.
- Define network SLOs and error budgets with product and customer-facing teams to prioritize reliability work.
- Build safe automation with blast-radius limits, staged rollouts, audit trails, and rollback capabilities.
- Establish operational standards for incident detection, handling, review, measurement, and learning.
- Build and lead the organization: hire, develop, and retain engineers and managers; design team structure as the network and org scale.
- Manage through leads and senior individual contributors with regular 1:1s, performance feedback, growth planning, and sponsorship.
- Partner with Network Engineering, Capacity Automation, Software, and Principal Engineers to embed reliability from the start.
- Partner with Data Center Operations, Supply Chain, and vendors on spares strategy and hardware failure trends.
- Represent the org's work, metrics, and technical direction to senior leadership, enterprise customers, and partners during incidents and reviews.
- Contribute to org-wide engineering process improvements.
Lambda has grown 10x over the last three years and is scaling its network engineering organization accordingly. This role reports to the VP of Cloud and AI Networking and works alongside a highly capable team of customer-obsessed engineers.
REQUIREMENTS:
- 8+ years of engineering management experience, including managing managers and directly managing senior individual contributors.
- Proven track record leading SRE, network reliability, or production operations organizations for large-scale cloud or data center networks with 24x7 availability requirements.
- Network or software engineering background with shipped production systems; ability to engage credibly on architecture, technical tradeoffs, and code quality.
- Demonstrated success reducing toil and incident impact through automation, with measurable data (e.g., lower time to restore, higher share of incidents remediated automatically).
- Familiarity designing, building, scaling, and operating large-scale networks, including routing (BGP), leaf-spine fabrics, optics, hardware failure modes, network telemetry, and monitoring.
- Experience building closed-loop or event-driven remediation systems with safety controls to prevent automation-induced incidents.
- Experience running incident management at scale: incident command, blameless postmortem culture, and shipping engineering work from lessons learned.
- Ability to foster data-driven, automation-first, high-velocity organizations.
- Track record building high-performing teams in fast-moving, technically demanding environments.
- Skill translating ambiguous business and product goals into clear team priorities and executable engineering plans.
- Strong judgment about when to go deep technically, when to delegate, and when to escalate.
- Calm, decisive demeanor during major incidents with clear communication to customers and executives.
- Excellent written and verbal communication; ability to use high-quality written artifacts to inform decision-making.
NICE TO HAVE:
- Experience in GPU cloud, HPC, or AI/ML infrastructure environments.
- Experience operating InfiniBand or RoCE fabrics at scale and understanding how network faults affect distributed training jobs.
- Experience applying ML or LLM-based tooling to operations (anomaly detection, alert correlation, automated triage, root-cause analysis).
- Experience with streaming network telemetry at scale (gNMI, OpenConfig, or similar).
