Software Engineer, Fullstack (AI)

Sprig•San Francisco, CA

43d•Hybrid

About The Position

Sprig's AI team builds the systems that help user-experience researchers and product managers understand their users at scale. We transform rich behavioral and feedback data into insights about product experiences. As a full-stack software engineer, you'll play a key role in shaping the systems that power these capabilities. Our work spans from distributed data processing and inference pipelines to the product surface that UX researchers and PMs interact with. The team operates across the stack but this role emphasizes front-end and API layers. You'll join a group that values pragmatic engineering, clear design, and measurable impact, advancing both our technical foundation and our ability to deliver trustworthy, privacy-safe analyses and insights. This is a hybrid role with three days working in our downtown San Francisco office, which is just a short walking distance from the Montgomery BART station.

Requirements

You have 2+ years of professional experience building and shipping production software.
You are comfortable developing across our stack: React, Node.js/Express, AWS, and PostgreSQL.
You have a solid understanding of data structures, RESTful APIs, SQL, and testable system design.
You are capable of designing, implementing, and maintaining well-scoped features or services end-to-end.
You communicate clearly, contribute to reviews and design discussions, and learn through feedback.
You are motivated to extend skills into distributed AI workflows, inference systems, and prompt and context engineering.

Nice To Haves

It is a plus if you are familiar with event-driven architectures and distributed data processing.

Responsibilities

Build and ship user-facing features - Develop UI components and backend APIs that help product and research teams understand user experiences at scale.
Own small features end-to-end - Take responsibility for well-defined product surfaces or API endpoints, from design and implementation to monitoring and iteration.
Collaborate and learn from experienced engineers - Work closely with senior teammates to review designs, debug complex issues, and grow your technical judgment.
Extend your impact into AI and data systems - Gain exposure to distributed data workflows, prompt engineering, and the AI inference systems that power Sprig's analyses and insights.
Contribute to quality and shared understanding - Write reliable, testable code, improve observability, and document designs so others can build confidently on your work.