Engineering Manager, Core Services at Lambda

San Francisco, California, United States

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$297,000 – $495,000Compensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Artificial Intelligence, Cloud ComputingIndustries

Requirements

7+ years of experience in either Release Engineering or Platform Engineering with at least 3 years in a management or lead role
Demonstrated experience leading a team of engineers and SREs on complex, cross-functional projects in a fast-paced startup environment
Experience managing, monitoring, and scaling CI/CD platforms
Deep experience using and operating AWS services
Solid background in software engineering and the SDLC
Strong project management skills, leading planning, project execution, and delivery

Responsibilities

Grow/hire, lead, and mentor a team of high-performing platform engineers and SREs
Foster a culture of technical excellence, collaboration, and customer service
Conduct regular one-on-one meetings, provide constructive feedback, and support career development for team members
Drive outcomes by managing project priorities, deadlines, and deliverables
Work with the engineering team to drive strategy for internal CI/CD and Cloud services
Develop self-service abstractions to make platform tooling easier to adopt and use
Lead the broader engineering organization in best-practices adoption of CI/CD, Workflow, and Cloud services
Manage costs of both vendors and internally developed platforms
Lead team in the continued development of existing CI/CD solutions based on Buildkite and Github Actions
Lead team in the expansion of Terraform / Atlantis infrastructure automation platform
Guide Lambda engineering in utilization of AWS services in line with technical standards
Guide team in problem identification, requirements gathering, solution ideation, and stakeholder alignment on engineering RFCs
Identify gaps in platform engineering posture and drive resolution
Lead the team in supporting internal customers from across Lambda engineering
Work closely with Lambda product engineering teams on requirements and planning to meet their needs
Work to understand the needs of engineering teams and drive Platform solutions towards self-service
Manage a short list of vendors that provide SaaS solutions used at Lambda

Skills

CI/CD

AWS

Release Engineering

Cloud Automation

SRE

Platform Engineering

Artifact Management

Lambda

Cloud-based GPU services for AI training

About Lambda

Lambda Labs provides cloud-based services for artificial intelligence (AI) training and inference, focusing on large language models and generative AI. Their main product, the AI Developer Cloud, utilizes NVIDIA's GH200 Grace Hopper™ Superchip to deliver efficient and cost-effective GPU resources. Customers can access on-demand and reserved cloud GPUs, which are essential for processing large datasets quickly, with pricing starting at $1.99 per hour for NVIDIA H100 instances. Lambda Labs serves AI developers and companies needing extensive GPU deployments, offering competitive pricing and infrastructure ownership options through their Lambda Echelon service. Additionally, they provide Lambda Stack, a software solution that simplifies the installation and management of AI-related tools for over 50,000 machine learning teams. The goal of Lambda Labs is to support AI development by providing accessible and efficient cloud GPU services.

San Jose, CaliforniaHeadquarters

2012Year Founded

$372.6MTotal Funding

DEBTCompany Stage

AI & Machine LearningIndustries

201-500Employees

Risks

Nebius' holistic cloud platform challenges Lambda's market share in AI infrastructure.

AWS's 896-core instance may draw customers seeking high-performance cloud solutions.

Existential crisis in Hermes 3 model raises concerns about Lambda's AI model reliability.

Differentiation

Lambda offers cost-effective Inference API for AI model deployment without infrastructure maintenance.

Nvidia HGX H100 and Quantum-2 InfiniBand Clusters enhance Lambda's AI model training capabilities.

Lambda's Hermes 3 collaboration showcases advanced AI model development expertise.

Upsides

Inference API launch attracts enterprises seeking low-cost AI deployment solutions.

Nvidia HGX H100 clusters provide competitive edge in high-performance AI computing.

Strong AI cloud service growth indicates rising demand for Lambda's GPU offerings.

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