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Creatify

Software Engineer, Applied AI / Product

San Francisco Bay AreafulltimemidAdded today

About this role

Join a healthcare startup building an AI-powered platform that combines medicine and law to help independent physicians manage complex casework. You'll develop across the full stack—from agent architectures and evaluation frameworks to data pipelines and user interfaces—shipping features that directly impact real clinical and legal workflows.

What you'll do

  • Design and deploy AI agent workflows that automate steps in medical-legal case processes
  • Build evaluation frameworks to ensure agent outputs are reliable before shipping to production
  • Architect data ingestion and retrieval systems that provide agents with the right case context
  • Develop user-facing interfaces and tooling that integrate agent capabilities into daily workflows
  • Iterate rapidly on features based on direct physician and operations team feedback
  • Establish patterns and infrastructure for AI-native development practices

What they're looking for

  • Full-stack software engineering (backend, frontend, infrastructure)
  • AI/LLM application development and prompt engineering
  • Evaluation frameworks and testing methodologies for AI systems
  • Data pipelines, indexing, and retrieval systems
  • Building for reliability and correctness in high-stakes domains
  • Rapid prototyping and shipping without detailed specifications
  • Healthcare or regulated industry domain knowledge (a plus)
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Creatify

Creatify builds an AI-powered video advertising platform that automates ad creation and distribution for major brands. The company is hiring Full-Stack Engineers, AI Research Engineers, Data Engineers, and Infrastructure/Platform Engineers to develop its SaaS product, data infrastructure, and cloud systems.

View all jobs at Creatify

Likely interview questions

  • Tell us about a time you shipped a complex feature end-to-end without a detailed specification—how did you approach the ambiguity?
  • Describe your experience building or evaluating AI systems. How do you think about reliability and safety?
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