Note: The job is a remote job and is open to candidates in USA. Tern is a venture-backed software company on a mission to reshape the travel agency industry by empowering small businesses with technology. The AI & Data Engineer will build and own the AI and data systems that are central to Tern's product, ensuring the reliability and quality of AI features and data pipelines.

Responsibilities

• Build and ship the systems behind Tern's AI features: the data infrastructure, services, and agentic tooling they run on. The output of this role is working software in production, not decks or recommendations
• Build the evaluation systems that answer whether an AI feature is good enough to ship and good enough to keep- eval harnesses, datasets, and production monitoring that run as software, not one-off analyses. Where no quality bar exists yet, build the thing that sets it
• Own data quality as a first-class concern across ingestion, modeling, and reporting. Catch problems before they reach a model, a dashboard, or a user. Fix them end to end
• Build and maintain the ETL systems that move and shape data from our application and third-party sources. Keep them reliable as volume grows
• Work alongside product squads to build the reporting that gives advisors and agency owners real visibility into how their business is performing
• Make the people around you faster and better. Share context early and write clearly so others can build on your work

Skills

• Production AI/ML experience- the must-have: You've built and shipped AI and/or ML systems that real users depended on in production, and you owned what happened after launch. Watching quality, debugging bad outputs, and making the system better over time. This matters more to us than any specific tool or title
• Evals as engineering: You treat evaluation as something you build, not a report you write. You have a real point of view on what to measure, how to catch drift and regressions, and when a metric is lying to you ideally from building evals for a production system
• Data pipeline and service ownership: You've personally built and owned pipelines and services that move data from application sources into a warehouse. You know what breaks, when and why, and you own the fix
• High agency: You've taken ambiguous, under-specified problems and driven them to a working outcome. You don't need a fully-scoped ticket to start
• Experience with Ruby on Rails or working directly from an application database rather than just downstream data
• Hands-on experience with LLM evaluation and observability tooling
• Experience with MCP-based tooling or agentic data workflows

Benefits

• Competitive salary, equity, and benefits package

Company Overview