Applied AI Engineer

About Cobalt

Cobalt is the infrastructure layer that makes healthcare AI possible. Dozens of high-growth companies rely on us as core infrastructure. We’re the reason their products can connect to healthcare systems at all. When they need to move fast, we’re the team they call.

We’ve built this with a lean, elite team that punches way above its weight. No bloat, no layers, no passengers. Every person here has outsized impact, and we intend to keep it that way as we scale. If you want to do the best work of your career at a company that’s growing fast and building something that actually matters, keep reading.

About the role

AI isn't a feature at Cobalt. It's how we build. We use AI internally to make our infrastructure smarter, faster, and more reliable. This role exists because we believe the companies that win will be the ones that embed AI into their core operations, not bolt it on later.

You'll build AI-powered systems that sit at the core of our platform: intelligent data mapping, automated integration pipelines, and models that make healthcare interoperability less painful. This isn't a research role. You'll ship production AI systems that handle real patient data at scale.

What you’ll do

• ›Build and deploy models for healthcare data normalization, mapping, and classification
• ›Design AI-powered automation for integration onboarding and maintenance
• ›Develop intelligent systems that reduce manual work across our platform
• ›Work with messy, real-world healthcare data and make it usable
• ›Evaluate and integrate foundation models where they solve real problems, not for show

What we’re looking for

• ›3+ years building production AI systems (not just notebooks)
• ›Strong software engineering skills. You can build the service, not just the model
• ›You've taken models from prototype to production and kept them running
• ›Deep intuition for when to use an LLM vs. a classical approach vs. a simple rule
• ›You move fast and care more about impact than architecture diagrams

Nice to have

• +Experience building agentic workflows or multi-step AI pipelines
• +Background in data integration or transformation systems
• +Healthcare industry exposure