Staff Software Engineer - Expert Contributor Lifecycle

Snorkel AI Snorkel AI · Data AI · Redwood City, CA +1 · 312 - Engineering

Staff Backend Engineer at Snorkel AI responsible for setting technical direction and strategy for the Expert Contributor (EC) Platform, focusing on the end-to-end EC lifecycle, including automated onboarding, performance management, and contributor retention. The role involves building robust features, integrating with third-party services, automating supply and allocation logic for ECs, prototyping and optimizing data user management pipelines, and setting strategy for build systems and CI/CD. This role also involves mentoring engineers and partnering with cross-functional teams to improve dev-infra, release processes, and internal tooling, with a focus on enabling domain experts to provide data for AI training and refinement.

What you'd actually do

  1. Design and develop mission-critical systems for the end-to-end Expert Contributor (EC) lifecycle, focusing on automated onboarding workflows, performance management, and contributor retention.
  2. Build robust features and integrations with key third-party services, including platforms for assessments and Employer of Record systems.
  3. Automate supply and allocation logic to efficiently manage and deploy a high volume of ECs to various data collection projects, ensuring optimal coverage and quality.
  4. Prototype, optimize, and maintain scalable services to power complex data user management pipelines.
  5. Set the strategy and architecture for build systems, testing frameworks, and CI/CD pipelines.

Skills

Required

  • 8+ years of software engineering experience developing performant, intuitive, and scalable web application architectures
  • 2+ years working at a Staff level or equivalent
  • Strong background in developer productivity
  • Strong background in distributed systems
  • Strong background in cloud platforms (AWS preferred)
  • Expertise designing REST for internal services and developers
  • Experience developing and shipping enterprise software products, specifically those focused on data collection, or machine learning applications
  • Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact
  • Ability to work in a fast-paced environment
  • strong technical communication skills

Nice to have

  • Experience in hyper-growth startup environments or scaling engineering orgs
  • Experience with AI development workflows
  • AI-assisted code generation
  • SRE automation
  • strong excitement to learn
  • Prior experience as a Tech Lead Manager (TLM) or equivalent role with a focus on cross-functional technical leadership and mentorship

What the JD emphasized

  • mission-critical systems
  • high volume of ECs
  • scalable services
  • enterprise software products
  • leading complex engineering initiatives

Other signals

  • transform expert knowledge into specialized AI at scale
  • enable domain experts to provide high-signal data for training and refining state-of-the-art models
  • data acquisition and refinement