Software Engineer — Cloud Infrastructure Optimization

We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!

We are looking for an engineer for our Infrastructure team to help us improve and manage the efficiency, usage, and cost of our cloud and overall infrastructure.

Primary Responsibilities

• Establish Snorkel’s FinOps engineering practice to drive centralized cost management and optimization strategies.
• Provide visibility into metrics, performance, usage, and cost across infrastructure and related SaaS tools used at Snorkel (e.g., Datadog, LaunchDarkly).
• Stay up-to-date on evolving cloud pricing models, available discounts, industry trends, and best practices across AWS, Azure, GCP, and beyond.
• Advise enterprise customers on understanding Snorkel’s product from an efficiency perspective and suggest optimization strategies.
• Contribute to the design and improvement of observability and alerting systems for Snorkel’s SaaS and PaaS platforms.
• Collaborate closely with infrastructure teams to continuously evolve our Kubernetes and broader cloud strategies.
• Partner with engineering teams to provide design suggestions that improve resource efficiency and reduce operational cost.
• Build dashboards, tools, and reports to highlight high-cost areas and forecast future expenses for leadership visibility.
• Contribute to Snorkel’s engineering culture through mentorship, open communication, user empathy, and advocacy of strong engineering practices.

Work a hybrid schedule, with three days per week in our Redwood City HQ or San Francisco office.

Minimum Qualifications

• Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
• Strong development and debugging skills in Python.
• 3+ years of experience in software development (academic experience included).
• Deep understanding of at least one major cloud provider (AWS, Azure, or GCP) and the Kubernetes ecosystem.
• Experience with optimization and desire to take ownership of our cloud workloads to identify inefficiencies and recommend cost-saving opportunities (e.g., optimizing EKS node utilization, recommending appropriate EC2 instance types, etc.).

Preferred Qualifications

Successful candidates will likely have most of the following. These are guidelines, not strict requirements:

• Strong experience in designing, building, and managing cloud infrastructure for enterprise platforms on AWS, GCP, or Azure (e.g., EC2, EKS, VPC).
• Experience working at high-growth technology startups, and able to balance agility and clarity with rigor and long-term sustainability.
• Proficient with infrastructure-as-code tools such as Terraform, CloudFormation, or Helm.
• Hands-on experience with CI/CD systems and test infrastructure for large, complex codebases.
• Familiarity with cloud cost monitoring and reporting tools such as Kubecost, AWS Cost Explorer, Datadog Cloud Cost Management, Cast AI, or similar

[Nice to have]:

• Hands-on experience working with LLMs and API providers such as OpenAI, Anthropic, and Amazon Bedrock.
• Experience creating and maintaining observability dashboards using platforms like New Relic, Datadog, or Grafana.
• Experience building and maintaining cost visibility dashboards for various cloud services.

The salary range for this position based in the San Francisco Bay Area is $172,000.00 - $240,000.00. All offers include equity compensation in the form of employee stock options.

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