Senior Cloud Solutions Engineer

Reposted 22 Hours Ago
San Francisco, CA
In-Office
251K-377K Annually
Senior level
Software
The Role
The Senior Cloud Solutions Engineer advocates for Lambda's cloud products, manages technical sales processes, deploys AI/ML workloads, and contributes to organizational culture with 8+ years of cloud infrastructure experience.
Summary Generated by Built In

Lambda, The Superintelligence Cloud, builds Gigawatt-scale AI Factories for Training and Inference. Lambda’s mission is to make compute as ubiquitous as electricity and give every person access to artificial intelligence. One person, one GPU.


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


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

  • Advocate for Lambda’s Products

    • Develop and maintain expertise in Lambda’s cloud products and services

    • Demonstrate Lambda’s software and solutions to customers, partners and staff

    • Create field enablement materials for technical audience, lead workshops and support product advocacy efforts

    • Provide technical feedback from customers to Lambda’s product and marketing teams

  • Own the technical side of Lambda’s sales process.

    • Partner with Lambda account executives to drive customer adoption and ensure successful delivery

    • Evaluate and assess customers needs to deeply understand pain-points, bottlenecks and expected outcomes

    • Recommend appropriate cloud services and configurations to design a cohesive solution that supports the customers applications and workflow

    • Document proposal and designs in formats including but not limited to presentations, white-papers, visuals, Bill of Materials and rack elevations

  • Demonstrate expertise on Lambda’s cloud infrastructure

    • Build structured and purposeful learning into your work routine

    • Develop and support internal Lambda community as a subject matter expert

    • Be an expert at deploying AI/ML workloads on Lambda cloud

    • Stay up to date on the latest deep learning trends, best practices and experiment with them using internal tools and resources

    • Develop high quality processes and documentation

  • Reinforce Lambda’s culture

    • Contribute positively throughout the organization

    • Maintain a high level of agility and responsiveness

    • Hyper-focused on customer satisfaction

You

  • Have 8+ years of experience designing, deploying and scaling cloud infrastructure

  • Have 4+ years of experience as a solutions architect or consultative capacity supporting cloud infrastructure and services

  • Have 3+ years of experience working with cloud-based AI/ML services

  • Have deep knowledge of the ML ecosystem, including common models, practical use cases, and supporting tools

  • Have experience building with modern infrastructure tools such as Docker, Kubernetes, Ansible and Terraform

  • Have deep knowledge of cloud infrastructure, security, networking, and cost optimization techniques

  • Have experience coding in Python, C# or similar programming language

  • Have experience developing with NVIDIAs GPUs

  • Have led complex technical projects with diverse stakeholders

  • Have demonstrated impact at an organizational/multi-departmental level

  • Have experience leading complex cloud deals, influencing C-level stakeholders, and mentoring junior SEs or architects

  • Thrive in dynamic settings and embrace radical ownership of initiatives and outcomes

Nice to Have

  • Experience with AI/ML use case to algorithm selection, training, tuning, inference, and training pipeline design and build.

  • Participation in go-to-market (GTM) initiatives or product launches

  • Experience working with LLM architectures

  • Experience working with RESTful API and general service-oriented architecture

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, ~400 employees (2025) and growing fast

  • We offer generous cash & equity compensation

  • Our investors include Andra Capital, SGW, Andrej Karpathy, ARK Invest, Fincadia Advisors, G Squared, In-Q-Tel (IQT), KHK & Partners, NVIDIA, Pegatron, Supermicro, Wistron, Wiwynn, US Innovative Technology, Gradient Ventures, Mercato Partners, SVB, 1517, Crescent Cove.

  • We are experiencing extremely high demand for our systems, with quarter over quarter, year over year profitability

  • Our research papers have been accepted into top machine learning and graphics conferences, including NeurIPS, ICCV, SIGGRAPH, and TOG

  • 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

A Final Note:

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.

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.

Top Skills

Ansible
C#
Docker
Kubernetes
Nvidia Gpus
Python
Terraform
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The Company
HQ: San Francisco, CA
106 Employees
Year Founded: 2012

What We Do

Lambda provides computation to accelerate human progress. We're a team of Deep Learning engineers building the world's best GPU workstations and servers. Our products power engineers and researchers at the forefront of human knowledge. Customers include Microsoft, MIT, Los Alamos National Lab, Disney, Tencent, Kaiser Permanente, Stanford, Harvard, Caltech, and the Department of Defense.

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