Staff Software Engineer - Managed Kubernetes

Lambda Inc.

Job Overview

Location

Bellevue, WA

Job Type

Full-time

Full Job Description

📋 Description

• Lead the technical vision and development of Lambda’s Managed Kubernetes platform, purpose-built for AI workloads on bare metal infrastructure, ensuring scalability, multi-tenancy, and high availability across tens of thousands of customer deployments.
• Design and implement GPU-aware orchestration systems by integrating and extending NVIDIA’s open-source ecosystem, including GPU Operator, Network Operator, DCGM, NCCL, AICR, and Topograph for topology-aware scheduling and placement.
• Drive the architecture and development of Managed Slurm on Kubernetes, enabling seamless coexistence of traditional HPC batch workloads and containerized AI workloads on the same platform.
• Design and build higher-level platform services for AI inference, including model serving infrastructure, dynamic autoscaling based on inference load, and multi-model deployment patterns.
• Define and implement networking solutions for AI workloads by collaborating with the Network team on CNI integration (Cilium, Multus), high-performance fabrics (InfiniBand, RoCE), RDMA, and GPUDirect.
• Partner with Storage teams to define storage architecture requirements for Managed Kubernetes, Slurm, and future services, ensuring optimal I/O performance for large-scale AI training and inference.
• Establish operational excellence for a managed service through automation of upgrades, security patching, zero-downtime maintenance, and infrastructure-as-code/GitOps workflows.
• Lead chaos engineering initiatives to validate system resilience under failure conditions at scale, ensuring platform reliability for mission-critical AI workloads.
• Build self-healing systems and automation for incident response, root cause analysis, and proactive platform resilience across distributed GPU clusters.
• Serve as the technical bridge between Orchestration and cross-functional teams (Network, Storage, Security), translating platform needs into actionable infrastructure specifications across the full stack.
• Drive infrastructure-wide decisions that align bare-metal provisioning, network topology, and storage systems with the requirements of managed orchestration services.
• Champion consistency and standardization across Lambda’s infrastructure stack, ensuring unified design patterns, monitoring, and operational practices.
• Mentor and grow engineers on the Orchestration team, establishing best practices in Kubernetes development, distributed systems, and Cloud Native engineering.
• Represent Lambda externally through technical blog posts, conference talks, and strategic customer engagements, contributing to the broader open-source community.
• Shape the AIOps vision by designing intelligent systems for automated capacity planning, anomaly detection, and predictive maintenance of cloud infrastructure.
• Collaborate directly with customers and internal teams to understand legacy deployments and chart migration paths to Lambda’s managed platform.
• Engage with NVIDIA and the open-source ecosystem to stay current on GPU orchestration technologies and contribute back to upstream projects where applicable.
• Design and implement secure, compliant multi-tenant environments with RBAC, Pod Security Standards, network policies, and workload isolation.
• Maintain deep expertise in Linux systems and networking (L2–L7), including high-performance networking concepts like RDMA and InfiniBand.
• Write production-quality code in Go and Python, with a focus on building scalable, maintainable, and elegant infrastructure systems.
• Drive design reviews and technical decision-making across teams to ensure systems are scalable, observable, and aligned with customer needs.
• Utilize modern tools and AI-assisted development (e.g., Claude Code) to accelerate productivity and increase engineering impact.

🎯 Requirements

• 10+ years of experience in software engineering, platform engineering, or SRE, with at least 5 years focused on Kubernetes at scale
• Expert-level understanding of Kubernetes internals: API machinery, controllers, schedulers, operators, CRDs, CSI, CNI, and extension patterns
• Strong software engineering skills in Go (required) and Python; production-grade coding experience
• Deep experience with GPU orchestration in Kubernetes: NVIDIA GPU Operator, device plugins, DCGM, MIG, time-slicing, and GPU-aware scheduling
• Proven track record of technical leadership: driving cross-team design decisions, mentoring engineers, and influencing infrastructure direction beyond immediate scope
• Hands-on experience designing and operating managed services or multi-tenant platforms

🏖️ Benefits

• 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 employees actively use
• Opportunity to work with NVIDIA’s cutting-edge open-source GPU and networking stack

Skills & Technologies

Python

Kubernetes

Linux

Prometheus

Grafana

Senior

Onsite

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Lambda Inc.

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About Lambda Inc.

Lambda Inc. provides cloud-based GPU clusters and workstations for artificial-intelligence research and development. The company designs and operates high-performance hardware infrastructure optimized for machine-learning workloads, offering on-demand access to NVIDIA GPUs, pre-configured deep-learning software stacks, and scalable storage. Customers include AI labs, universities, and enterprises training large language and computer-vision models. Founded in 2012, Lambda is headquartered in San Francisco and maintains data centers across North America and Europe.

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