Senior Applied AI Engineer

Komodo Health•New York, NY

64d•$191,000 - $253,000•Hybrid

About The Position

Komodo Health is transforming healthcare by building the leading healthcare analytics platform. Our AI team, Labs@Komodo, is pioneering this transformation by delivering AI-native solutions that elevate both the products we bring to market and the way we build them. This role is designed for engineers who thrive in a fast loop of experimentation, iteration, and validation—people who move quickly from idea to working prototype using AI tools, and who know when to slow down and apply engineering discipline to scale what works. We’re looking for engineers who approach AI like product managers—owning the full lifecycle of intelligent systems: from rapid prototyping to feedback-driven iteration to scalable deployment, with a deep focus on how these systems deliver value, evolve over time, and integrate across the broader product ecosystem. You’ll serve as a multiplier: accelerating Komodo’s external innovation while reshaping internal systems, from engineering workflows to business automation. Looking back on your first 12 months at Komodo Health, you will have accomplished… Delivered production-ready AI products and models that materially improve the precision and scalability of Komodo’s core analytics platform Rapidly prototyped and launched internal AI agents that enhance engineering workflows, automate routine tasks, and streamline cross-functional operations Helped shape and operationalize Komodo’s AI strategy by embedding AI-native thinking across products, teams, and platforms 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.

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: You are fluent across modern front-end frameworks such as React or Vue and back-end systems like FastAPI, Django, or Flask, and you use that breadth to design the APIs, interfaces, and services that bring AI capabilities into production.
End to end product ownership: You have a track record of translating customer or business needs into clear product requirements and delivering full stack features that turn AI prototypes into usable, value-driving products
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
A system-builder mindset: equally 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
This role is AI-native by design—you are expected to apply GenAI, agent-based workflows, and cutting-edge models as your default problem-solving toolkit.
Automating your own workflows using tools like Gemini, GPT, Claude, etc. and internal agents
Driving experimentation and adoption of new AI techniques within your team and across Komodo
Thinking in systems: understanding how prompt chains, orchestration logic, and fine-tuning loops can be built into scalable solutions

Nice To Haves

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.

Responsibilities

Designing and delivering AI-native products and tools that solve real healthcare challenges and optimize internal workflows.
Building and extending AI features across the full stack to ensure AI capabilities are production-ready and integrated into Komodo’s platform.
Driving 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.
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.
Transitioning successful prototypes into robust, scalable systems—with attention to reproducibility, observability, and maintainability.
Continuously exploring emerging models and toolchains (e.g., Gemini, GPT, Claude, open-source agents) and evaluating them through practical application.