Software Engineer III - Backend & Data Systems (AI Solutions)

Job description

Job responsibilities

• Own the backend services, APIs, and data models behind the tools our team builds, primarily in Python, holding the technical-design and code-review bar as they grow.
• Build integrations that bring product data together from our enterprise systems, reconciling sources that describe the same things in different ways.
• Improve, harden, and modernize existing applications — not just greenfield work — including auth, data integrity, testing, and technical debt.
• Shape our product data so AI features can actually use it: structure, naming, and context a model can navigate reliably — plus human-in-the-loop safeguards and the evaluations that show whether those features are…
• Deploy and operate the team's services on our cloud infrastructure (AWS), including CI/CD, monitoring, day-to-day reliability, and a share of on-call.
• Spend time with Manufacturing Engineers to learn how their work actually flows, and use data to validate that what you ship is actually helping the engineers who use it.

Job requirements

• Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent practical experience)
• 5+ years of software engineering experience, with demonstrated ownership of production backend services
• Strong backend and API development in Python or a comparable language (REST and/or GraphQL), including interfaces that applications and AI agents both build on
• Depth in relational data modeling and SQL — changing a schema and migrating data in production without breaking the applications built on it
• Experience integrating multiple systems of record: reconciling identifiers, handling incomplete or inconsistent data, and building pipelines that recover cleanly from partial failure
• Hands-on experience deploying and running applications on AWS and containerized infrastructure
• Comfortable integrating LLMs into products, with judgment about what data a model can actually work with and whether an AI-assisted system is genuinely working — designing evaluations, questioning flattering results,…
• Strong communication and cross-functional collaboration; able to work directly with non-technical users to turn their needs into working software