Senior Software Engineer - Developer Experience

Snorkel AI•San Francisco, CA

About The Position

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, 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! About the Role We are hiring a senior engineer to join our Developer Experience (DevEx) team — a small, high-impact group responsible for elevating how engineering builds, tests, ships, and collaborates. This role is ideal for someone who wants to own strategy, influence engineering-wide workflows, and grow into a Tech Lead Manager (TLM) You’ll shape our AI-native development environment , modernize CI/CD platforms (CircleCI, Buildkite, GitHub Actions), integrate AI SRE tooling, and mentor engineers across levels. Your work will directly accelerate developer velocity, reliability, and product quality across the company.

Requirements

8+ years of software engineering experience , including deep ownership of build, test, or CI/CD systems
Proven experience owning and evolving CI/CD systems for large-scale codebases, focusing on reliability, scalability, and developer productivity
Demonstrated experience defining and executing roadmaps for developer experience initiatives and internal engineering tooling
Deep understanding of how to effectively integrate AI agents into the development workflow to accelerate engineering velocity and improve developer experience.
Strong background in developer productivity , distributed systems , and cloud platforms (AWS preferred)
Track record of leading complex engineering initiatives , influencing stakeholders, and delivering measurable impact
Excellent communication skills; able to translate technical constraints into clear plans for non-technical audiences
Comfortable working with: Infra & deployment technologies: Terraform, Docker, Kubernetes CI/CD systems: CircleCI, Buildkite, GitHub Actions, Helm Build systems like Poetry, pip, uv
Experience designing and operating large-scale developer workflows and improving engineering best practices.

Nice To Haves

Experience in hyper-growth startup environments or scaling engineering orgs.
Experience with AI development workflows , AI-assisted code generation, or SRE automation or strong excitement to learn.
Prior experience as a Tech Lead , Team Lead , or Hands on Engineering Manager .

Responsibilities

Set the strategy and architecture for our local development environment, build systems, testing frameworks, CI/CD pipelines, and AI-assisted coding workflows (Claude Code, Claude MD-in-repo workflows)
Own the CI health and experience, maintain metrics to track CI health, developer productivity, effective usage of AI and build roadmap to constantly improve
End-to-end ownership of our release pipeline and lead the transition from scheduled releases to a robust, automated continuous deployment framework
Deep experience and opinion in standardizing for effective usage of AI coding and reviewing agents for faster development, review and incident investigation
Ship a clear multi-quarter DevEx roadmap and lead cross-team adoption
Mentor and technically guide engineers within and outside of the team with best practices to improve quality and velocity; potential to grow into TLM ownership as the team grows
Partner with cross-functional teams to design and deliver improvements to dev-infra, release processes, and internal tooling. Proactively identify bottlenecks and drive large-scale DX initiatives — e.g., cutting flaky tests, improving PR iteration speed, increasing automated test coverage, and reducing infra cost
Present plans, tradeoffs, and progress to engineering leadership; serve as a thought partner for org-wide developer experience strategy.
Champion experimentation and roll-out of AI-native development workflows, coding assistants, test-generation tools, and autonomous CI bots.

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