Komodo Health is transforming healthcare by building the leading healthcare analytics platform, and their AI team, Labs@Komodo, is pioneering this transformation by delivering AI-native solutions that elevate both the products they bring to market and the way they build them. The role is designed for engineers who can accelerate Komodo’s external innovation while reshaping internal systems, from engineering workflows to business automation.
Requirements
- A track record of building AI-powered systems that move rapidly from prototype to production.
- Strong proficiency with LLMs, prompt engineering, agent orchestration (LangChain, CrewAI, etc.), and multi-agent systems.
- Fluency in Python and hands-on experience with ML toolkits (e.g., PyTorch, HuggingFace, scikit-learn).
- Deep understanding of AI/ML fundamentals, with applied experience solving real-world problems using an AI-first approach.
- Comfort building quick demos, debugging AI behavior, and translating ideas into functional agent workflows or model pipelines.
- The engineering discipline to test, refactor, and scale systems with reliability, observability, and maintainability in mind.
- Experience leveraging AI Coding assistant tools like Cursor, ClaudeCode, Kilo, GitHub Co-Pilot etc.
Responsibilities
- Designing and building AI-native products and tools that address both market-facing healthcare challenges and internal workflow optimization.
- Driving experimentation by developing working demos and iterating based on fast feedback from users and data.
- Prototyping rapidly using GenAI models, chaining techniques, and orchestration frameworks to test ideas in days—not quarters.
- Partnering with engineers, product teams, and operational stakeholders to identify AI leverage points across workflows.
- Researching and applying state-of-the-art AI techniques—LLMs, agent-based systems, generative models, etc.—to both structured and unstructured datasets.
- Building internal systems that enhance developer productivity: think agents for code review, documentation generation, or dynamic prompt libraries.
- Architecting scalable ML infrastructure and maintaining high standards of reproducibility, explainability, and observability.
Other
- Mentored others in using AI to solve real problems by sharing best practices in prompt design, agent orchestration, and rapid iteration.
- Contributed to Komodo’s IP portfolio by building novel workflows that combined speed, creativity, and technical rigor.
- Set new standards for ethical, trustworthy AI by implementing feedback loops, model governance, and transparency mechanisms across your work.
- Strong communication and collaboration skills—able to work across technical teams and influence non-technical stakeholders.
- Degree in Computer Science, Machine Learning, or a related field—or equivalent hands-on experience that speaks for itself.
