Software Engineer
We're looking for a Software Engineer focused on designing and building scalable technical solutions. This lead role requires 4+ years of relevant experience.
About SuperAnnotate
SuperAnnotate helps the world’s leading AI teams build responsible, next-generation models powered by high-quality human data. We’re a fast-growing Series B startup bridging the gap between advanced AI innovation and the data that drives it. Our global network of expert specialists, scalable managed operations, precise talent matching, and full project transparency ensure unmatched data quality at scale. Trusted by innovators like Databricks and ServiceNow - and backed by NVIDIA, Dell Technologies Capital, Databricks Ventures, Cox Enterprises, and Lionel Messi’s Play Time VC - SuperAnnotate is proud to be the top-ranked AI data company on G2 for multiple consecutive years, including 2025.
The Impact You'll Make
We're looking for a technical operator who can own SuperAnnotate's most complex AI data programs end-to-end, from scoping and data design through delivery, quality, and client-facing problem solving.
This role is for someone who likes working directly with researchers and engineering teams, can debug messy data workflows, and wants meaningful ownership at the intersection of customer delivery, systems design, and AI model quality. You'll run the largest LLM and Gen AI data programs at SuperAnnotate, acting as a trusted technical resource to client researchers, diagnosing data quality issues, and reallocating resources under tight deadlines.
You won't be training models yourself, but you'll need enough technical depth to inspect data, debug workflows, understand evaluation tradeoffs, and speak credibly with ML researchers and engineers.
This is a full-time, hybrid position based in San Francisco.
What You'll Do
Own project delivery end-to-end. Lead LLM and Gen AI data engagements from initial scoping through final delivery, including use case definition, resource planning, quality oversight, and client sign-off. You'll be accountable for delivery quality, client trust, and program success.
Be the client's main technical point of contact. Build and maintain trusted relationships with researchers and engineering stakeholders. Bring transparency, good judgment, and a solutions orientation to every interaction.
Work hands-on with data and code. Write Python and SQL to inspect data, debug pipeline and schema issues, and spot quality problems before they reach the client. Build lightweight tooling and automate QA or reporting where it saves the team time.
Design and build the systems that make delivery possible. Architect data pipelines, quality frameworks, and review infrastructure that let your team execute at scale. Instrument the right KPIs, catch regressions early, and refine processes as program needs evolve.
Drive operational discipline across workstreams. Manage timelines, staffing plans, and delivery quality across multiple concurrent projects. Catch problems before they become crises.
Lead and develop yo
Posted July 10, 2026