---
title: 'Senior Site Reliability Engineer - SDN at Lambda'
canonical: 'https://feeny.ai/job/senior-site-reliability-engineer-sdn-lambda-san-francisco-92rvy8r6stxx'
type: 'job'
last_seen: '2026-09-13'
---

# Senior Site Reliability Engineer - SDN at Lambda

- **Company:** Lambda
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** hybrid
- **Posted:** 2026-07-07
- **Last confirmed live:** 2026-09-13
- **Apply:** https://jobs.ashbyhq.com/lambda/ee0998db-4bc2-44ea-9eee-4546109e4c3d

## Job description

Lambda, The Superintelligence Cloud, is a leader in AI cloud infrastructure serving tens of thousands of customers. Our customers range from AI researchers to enterprises and hyperscalers. Lambda's mission is to make compute as ubiquitous as electricity and give everyone the power of superintelligence. One person, one GPU.

If you'd like to build the world's best AI cloud, join us.

*Note: This position requires presence in our San Francisco/San Jose/Bellevue office location 4 days per week; Lambda’s designated work from home day is currently Tuesday.

Engineering at Lambda is responsible for building and scaling our cloud offering. Our scope includes the Lambda website, cloud APIs and systems as well as internal tooling for system deployment, management and maintenance.

## What You'll Do

- Operate and scale Lambda’s multi-tenant cloud networking platform and SDN infrastructure
- Operate and improve Kubernetes-based control plane services and dataplane software running on SmartNICs
- Develop tooling and automation to reduce operational toil and improve reliability
- Collaborate with software, platform, and networking teams to improve service reliability and deployment workflows
- Deploy and maintain network monitoring, observability, and management tools
- Improve deployment safety through CI/CD pipelines, GitOps workflows, testing, and progressive rollouts
- Drive operational excellence through observability, incident management, capacity planning, postmortems, and participation in the on-call rotation

You

- Have 5+ years of experience in Site Reliability Engineering, Production Engineering, or a similar role
- Have experience operating and supporting large-scale distributed systems in production
- Have experience with Kubernetes application lifecycle management, upgrades, troubleshooting, and production operations
- Have experience participating in on-call rotations and incident response
- Have strong troubleshooting skills across Linux systems, Kubernetes, distributed systems, and networking
- Have experience with observability platforms, monitoring, alerting, and metrics
- Are comfortable working on the Linux command line and have a solid understanding of the Linux networking stack
- Have experience with multi-datacenter and hybrid cloud environments
- Have experience automating infrastructure and operational workflows using Python, Ansible, or similar tools
- Have experience designing and operating CI/CD and GitOps deployment workflows

## Nice To Have

- Experience building and operating Software Defined Networks (SDN), including OpenStack Neutron, OVN, and OVS
- Experience operating production-scale SDNs in a cloud environment (e.g., infrastructure powering AWS VPC-like networking services)
- Software development experience in Go and/or Python (C is a plus)
- Experience automating infrastructure and network configuration using Kubernetes, Helm, Terraform, and Ansible
- Deep understanding of the Linux networking stack and its interaction with network virtualization technologies, SR-IOV, and DPDK
- Understanding of the SDN ecosystem and modern cloud networking architectures
- Experience diagnosing complex production issues across infrastructure, networking, and application layers

Salary Range Information The annual salary range for this position has been set based on market data and other factors. However, a salary higher or lower than this range may be appropriate for a candidate whose qualifications differ meaningfully from those listed in the job description.

## About Lambda

- Founded in 2012, with 500+ employees, and growing fast
- Our investors notably include TWG Global, US Innovative Technology Fund (USIT), Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, Gradient Ventures, Mercato Partners, SVB, 1517, and Crescent Cove
- We have research papers accepted at top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG
- Our values are publicly available: https://lambda.ai/careers
- We offer generous cash & equity compensation
- Health, dental, and vision coverage for you and your dependents
- Wellness and commuter stipends for select roles
- 401k Plan with 2% company match (USA employees)
- Flexible paid time off plan that we all actually use

## Equal Opportunity Employer

Lambda is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.

## About Lambda

## Company Overview
- **One-liner**: Lambda builds supercomputers and cloud infrastructure for training and deploying large-scale AI models, from single GPUs to gigawatt-scale AI factories.
- **Entity Type**: Private (funding stage not publicly disclosed; founded by ML engineers)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2012
- **Founders**: Stephen Balaban and Michael Balaban

## Core Business
- Primary industry: AI infrastructure / cloud computing for machine learning.
- Target customers: Frontier AI labs building large foundation models, hyperscalers scaling global AI infrastructure, and enterprises deploying AI in regulated industries (B2B, Enterprise).
- Mission: “Make compute as ubiquitous as electricity and give everyone in America the power of superintelligence” (also “One person, one GPU”).

## Products & Services
- **The Superintelligence Cloud**: A suite of cloud computing offerings specifically built for AI workloads, including:
  - **GPU Instances**: On-demand NVIDIA HGX B200, H100, and GB300 NVL72 instances for prototyping and testing.
  - **Managed Clusters**: Dedicated, single-tenant clusters (e.g., NVIDIA GB300 NVL72, HGX B200/H100) with full management and co-engineering from Lambda’s team.
  - **1-Click Clusters™**: Rapidly deployable clusters for training and inference.
  - **Superclusters**: Large-scale AI factories integrating high-density power, liquid cooling, and high-bandwidth interconnects.
- **AI Infrastructure Hardware**: Modular AI factory designs and NVIDIA-based systems for on-premise or colocation deployment.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed.
- **Key Metric**: Total funding not publicly available; revenue not disclosed.
- **Notable Customers/Partners**: “World’s most advanced AI organizations” (frontier labs, hyperscalers, regulated enterprises). Leadership includes former executives from cloud and networking companies.
- **Growth Signals**: Active hiring across engineering, storage, security, and procurement roles; building AI factories at gigawatt scale; SOC 2 Type II certified; expanding from San Francisco to San Jose, CA.

## Competitive Advantages
- **AI‑First DNA**: 100% of engineering, operations, and support dedicated to AI – founded by ML engineers in 2012.
- **Single‑Tenant Isolation**: Shared‑nothing architecture for security and performance, with hardware‑level isolation.
- **Full‑Stack Expertise**: Co‑engineering from the same team building the infrastructure, enabling deep optimization for large training runs.
- **Hacker Culture**: Rooted in the Noisebridge hackerspace values of do‑ocracy, low ego, and “be excellent to each other.”
- **Performance**: Rack‑scale NVIDIA systems (GB300, B200, H100) with high‑speed interconnects (NVIDIA Quantum‑2 InfiniBand).

## Strategic Focus
- Scaling infrastructure to support the next generation of superintelligence, including gigawatt‑scale AI factories.
- Enabling frontier labs to train trillion‑parameter models and serve billions of tokens in production.
- Expanding compliance and security capabilities for regulated industries.
- Growing the cloud platform (The Superintelligence Cloud) as the primary go‑to‑market offering.

## Why Work Here
- **Culture**: Hacker ethos (Noisebridge roots), low ego, no yelling, no politics, no crypto. Values: build, move fast, care, be excellent to each other.
- **Work Environment**: Fast‑paced, high‑change, outcome‑focused. Emphasis on technical excellence and curiosity. Anonymous feedback encouraged.
- **Interview Process**: Clear, structured steps (recruiter chat → hiring manager → technical assessment → panel interviews → reference/offer). Pedigree is not everything; focus on what you’ve built.
- **Location & Remote**: Offices in San Francisco and San Jose, CA. FAQ page addresses remote/hybrid policy (details not provided in available snippets); some roles appear on‑site.
- **Perks**: Benefits, time off, and other perks are listed on the careers site (specifics not extracted here).

## Sources
1. [lambda.ai/about](https://lambda.ai/about)
2. [lambda.ai/](https://lambda.ai/)
3. [lambda.ai/careers](https://lambda.ai/careers)
4. [lambda.ai/leadership](https://lambda.ai/leadership)

## Other roles at Lambda

- [Principal Network Engineer](https://feeny.ai/job/principal-network-engineer-lambda-bellevue-cc446qzny6m9) — Bellevue, WA
- [Director, Network Capacity Automation](https://feeny.ai/job/director-network-capacity-automation-lambda-bellevue-fyktn50b3wpw) — Bellevue, WA
- [Staff Mechanical Engineer - Data Center Cooling](https://feeny.ai/job/staff-mechanical-engineer-data-center-cooling-lambda-san-francisco-njgc53mgnewv) — San Francisco, CA
- [Senior Director, Product Management - Foundations](https://feeny.ai/job/senior-director-product-management-foundations-lambda-bellevue-jey21bq5wc6r) — Bellevue, WA
- [Staff Data Center Implementation Manager](https://feeny.ai/job/staff-data-center-implementation-manager-lambda-united-states-jyfexyg9by63) — United States
- [Senior Manager, Detection and Response](https://feeny.ai/job/senior-manager-detection-and-response-lambda-bellevue-f6jvw1b07xwk) — Bellevue, WA
- [Data Center Construction Site Foreman (Dallas)](https://feeny.ai/job/data-center-construction-site-foreman-dallas-lambda-united-states-vc7fg15nb275) — United States
- [Construction Administrator](https://feeny.ai/job/construction-administrator-lambda-san-jose-ky6swv0mtr9v) — San Jose, CA
- [Commodity Sourcing Manager – AI Infrastructure](https://feeny.ai/job/commodity-sourcing-manager-ai-infrastructure-lambda-san-jose-9zfy7qfg5bw5) — San Jose, CA
- [Data Center Operations Systems Engineer (San Jose)](https://feeny.ai/job/data-center-operations-systems-engineer-san-jose-lambda-san-jose-qabp07hbyq33) — San Jose, CA