Design and deliver AI-native products and tools that solve real healthcare challenges and optimize internal workflows.
Build and extend AI features across the full stack to ensure AI capabilities are production-ready and integrated into Komodo’s platform.
Drive the full product lifecycle by gathering requirements, shaping them into technical designs, and delivering complete features that connect AI systems to real customer and business value.
Drive experimentation by developing working demos and iterating based on fast feedback from users and data.
Prototype rapidly using GenAI models, chaining techniques, and orchestration frameworks to test ideas in days—not quarters.
Partner with engineers, product teams, and operational stakeholders to identify AI leverage points across workflows.
Research and apply state-of-the-art AI techniques—LLMs, agent-based systems, generative models, etc.—to both structured and unstructured datasets.
Build internal systems that enhance developer productivity: agents for code review, documentation generation, or dynamic prompt libraries.
Transition successful prototypes into robust, scalable systems—with attention to reproducibility, observability, and maintainability.
Continuously explore emerging models and toolchains (e.g., Gemini, GPT, Claude, open-source agents) and evaluate them through practical application.
Mentor others in using AI to solve real problems by sharing best practices in prompt design, agent orchestration, and rapid iteration
Requirements
A track record of building AI-powered systems that move rapidly from prototype to production
Strong proficiency with LLMs, prompt engineering, context engineering, agent orchestration, and multi-agent systems
Fluency in Python and hands-on experience with Gen AI frameworks (Chat Completions API, vLLM, Crew AI, Strands, etc.)
True full stack engineering: fluent across front-end frameworks such as React or Vue and back-end systems like FastAPI, Django, or Flask
End to end product ownership: translating customer or business needs into clear product requirements and delivering full stack features
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
Engineering discipline to test, refactor, and scale systems with reliability, observability, and maintainability
System-builder mindset: motivated to craft internal AI tools and deliver customer-facing solutions
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
Expected to apply GenAI, agent-based workflows, and cutting-edge models as your default problem-solving toolkit
Experience with specific healthcare data modalities (e.g., claims, EHR, genomic data)
Experience with distributed computing frameworks (e.g., Spark, Snowflake, Databricks) for large-scale data processing
Benefits
This position may be eligible for performance-based bonuses as determined in the Company’s sole discretion and in accordance with a written agreement or plan.
This role may be eligible for equity awards.
Comprehensive health, dental, and vision insurance
Flexible time off and holidays
401(k) with company match
Disability insurance and life insurance
Leaves of absence in accordance with applicable state and local laws and regulations and company policy
Competitive total rewards package
Prepaid legal assistance
Paid time off for vacation, sickness, holiday, and bereavement
100% company-paid life insurance and long-term disability insurance
Hybrid work model with remote options and flexibility
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.