Data Engineer

Popai Health is a fast-growing health tech startup transforming the way care teams engage with patients. We build AI tools that analyze phone conversations between care managers and patients, surfacing insights, automating documentation, and helping close care gaps—so teams can focus on what matters most: delivering better care.

What you'll do:

• Design and scale intelligent data pipelines - workflows that behave like decision trees, with branching logic, and context-aware routing and dynamic nodes powered by LLMs
• Build a next-generation data platform that lets non-developers (and eventually users) create, test, and deploy complex pipelines independently.
• Innovate on data modeling and storage design: create robust strategies for storing the results of multi-branch pipeline nodes to enable high-performance downstream consumption, aggregations, and intelligent search over unstructured text.
• Design and build cloud-native data systems that leverage the cloud rich capabilities for scale, performance, and reliability.
• Own the full development lifecycle - from requirements and design to deployment and ongoing maintenance.
• Collaborate with stakeholders to translate their needs into technical requirements and features and product features.
• Stay at the forefront of tech by integrating state-of-the-art tools and LLMs that expand our system’s intelligence and performance
• Build monitoring & logging capabilities to ensure smooth operations.

What we’re looking for:

• 8+ years of hands-on experience building data systems in production.
• Deep understanding of data engineering, distributed systems, and workflow orchestration.
• Strong software engineering & architecture skills (OOP, SOLID, system & code design, microservices).
• Experience with AWS & cloud-native development.
• Bonus: Hands-on experience with LLMs & NLP.