Engineering Manager, Lambda

• Extensive experience in HPC or large-scale infrastructure, including at least 3 years in a leadership or management role
• Work well under deadlines and structured project plans; able to successfully (and tactfully) negotiate changes to project timelines
• Have excellent problem solving and troubleshooting skills
• Can effectively collaborate with peer engineering managers to coordinate efforts that may impact deployment operations
• Are comfortable leading and mentoring HPC engineers on cluster deployments as needed
• Experience building a high-performance team through deliberate hiring, upskilling, planned skills redundancy, performance-management, and expectation setting
• Have flexibility to travel to our North American data centers as on-site needs arise or as part of training exercises
• You do not need to match all of the listed expectations to apply for this position. We are committed to building a team with a variety of backgrounds, experiences, and skills

Desirable

• This position requires presence in our San Francisco/San Jose or Seattle 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
• Ngineering at Lambda is responsible for building, operating, scaling and maintaining our AI Cloud offerings. The HPC Deployments team are responsible for deploying cutting edge NVIDIA GPU clusters on time, at scale and with 100% quality & correctness
• Reporting to the Director of Fleet Engineering, you will lead and scale one of our HPC Deployments teams. This work is highly cross functional and critical to the timely success of our customers
• Your team is focused on building and validating clusters deployed across our data center facilities. You will work collaboratively with Product and Infrastructure engineering teams to improve transparency, metrics, automation and overall efficiency for the team
• Lead and grow a distributed top-talent team of HPC engineers responsible for the configuration, validation, deployment of large scale GPU clusters
• Work cross functionally with teams in the organization to deliver projects and deployments on time, ensuring alignment across stakeholders
• Identify opportunities for efficiency improvements in the tools / process / automation that the team relies upon day to day
• Ensure stakeholders have clear visibility into deployment progress, risks, and outcomes
• Drive outcomes by managing staff allocations, project priorities, deadlines, and deliverables
• Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members
• Stay current on the latest HPC/AI technologies and best practices
• Participate in the qualification efforts of new technologies for use in our production deployments