Full-Stack AI Engineer (evergreen)
komodohealth • San Francisco, CA
Posted: June 16, 2026
Job Description
Of note, this role will remain posted until July 17, so we have time to review applications thoughtfully. Once all current resumes have been reviewed, the role will be reposted as needed.
The Opportunity at Komodo Health:
Healthcare in the U.S. is a mess. Komodo Health is fixing that—with data. We've mapped the patient journey across the country to build the most complete picture of disease burden and treatment gaps. Our customers—pharma companies, payers, and health systems—use this data to make decisions that meaningfully improve patient outcomes.
Labs@Komodo builds the AI-native platforms and systems that turn this data into action. We are the team behind Marmot, Komodo's AI-native product—designed with AI embedded directly into both the interface and the development workflow. By combining Komodo's unmatched healthcare data with modern LLMs, Marmot is delivering some of the most compelling real-world insights of the new AI era.
Building Marmot has sharpened our view of what this discipline actually demands. AI is rewriting what "full-stack" means — the engineers who excel here own the entire intelligence stack: data context and lineage, semantic definitions and business logic, retrieval and tool use, agent orchestration, evals and regression testing, model and prompt versioning, and permissions and governance. And they bring the product intuition to connect all of it to real outcomes. In healthcare, the stakes are higher still — AI systems must function amid messy real-world data, domain-specific definitions, privacy constraints, and high-stakes clinical and commercial decisions. Trustworthiness isn't a nice-to-have. It's the product.
Mission of the Role:
As a Full-Stack AI Engineer, you will design and deploy end-to-end AI solutions that power real products and internal tools. You'll work at the intersection of applied research, engineering, and product development — bringing modern AI techniques into scalable production systems.
You'll operate in a lean, high-leverage pod: a small team of Full-Stack AI Engineers paired closely with a PM who deeply understands the customer workflow — built to compress the discovery loop and ship things that actually matter. You'll also collaborate with platform and data teams to build AI capabilities that transform how healthcare data is explored, understood, and operationalized.
Looking back on your first 12 months at Komodo Health, you will have accomplished…
- Shipped production AI features that improve the precision, usability, and intelligence of Komodo's platform.
- Designed and deployed agent-based AI pipelines integrated into real customer-facing products.
- Built internal AI productivity tools that accelerate engineering workflows across Komodo.
- Prototyped and validated new AI approaches using emerging research and model capabilities.
- Contributed reusable prompt templates, orchestration patterns, and AI system architecture.
- Implemented monitoring, evaluation, and observability frameworks for deployed AI services.
What You'll Own:
- Designing, building, and deploying end-to-end AI systems across the full intelligence stack — from data context and retrieval to agent orchestration, evals, versioning, and governance.
- Developing agent pipelines, prompt chains, and orchestration frameworks for LLM-driven workflows.
- Selecting the right AI technique (LLMs, classic ML, or hybrid approaches) for the problem at hand.
- Collaborating with PMs, engineers, and data scientists to define requirements and deliver solutions.
- Building scalable AI services with monitoring, evaluation, and deployment pipelines.
- Contributing reusable patterns to Komodo's AI infrastructure and internal tooling ecosystem.
What you bring to Komodo Health (required):
- Experience building production-grade AI systems or AI-powered applications.
- Strong proficiency in Python.
- Experience working with LLMs, prompt engineering, or agent-based architectures.
- Familiarity with modern GenAI tooling and frameworks: vLLM, CrewAI, Strands, OpenAI / Chat Completions APIs.
- Ability to integrate AI capabilities across backend services and product interfaces.
- Experience designing evaluation frameworks, testing strategies, or monitoring systems for AI features.
- Strong collaboration skills across engineering, product, and data teams.
Expectations of AI Use in this role (required):
- At Komodo, AI is core to how we build. Full-Stack AI Engineers are expected to actively experiment with new AI techniques, share learnings across teams, and contribute to evolving best practices for building reliable, scalable AI systems. You will play a key role in shaping Komodo's AI-first engineering culture.
Additional skills and experience we’d prioritize (nice to have)…
- Healthcare data expertise.
- Experience with distributed computing frameworks (e.g., Spark, Snowflake, Databricks) for large-scale data processing.
*Compensation bands are inclusive of two levels
**Location flexible: NYC or SF hybrid, or remote
***Of note, this role will remain posted until July 17, so we have time to review applications thoughtfully. Once all current resumes have been reviewed, the role will be reposted as needed.
Additional Content
Of note, this role will remain posted until July 17, so we have time to review applications thoughtfully. Once all current resumes have been reviewed, the role will be reposted as needed.
The Opportunity at Komodo Health:
Healthcare in the U.S. is a mess. Komodo Health is fixing that—with data. We've mapped the patient journey across the country to build the most complete picture of disease burden and treatment gaps. Our customers—pharma companies, payers, and health systems—use this data to make decisions that meaningfully improve patient outcomes.
Labs@Komodo builds the AI-native platforms and systems that turn this data into action. We are the team behind Marmot, Komodo's AI-native product—designed with AI embedded directly into both the interface and the development workflow. By combining Komodo's unmatched healthcare data with modern LLMs, Marmot is delivering some of the most compelling real-world insights of the new AI era.
Building Marmot has sharpened our view of what this discipline actually demands. AI is rewriting what "full-stack" means — the engineers who excel here own the entire intelligence stack: data context and lineage, semantic definitions and business logic, retrieval and tool use, agent orchestration, evals and regression testing, model and prompt versioning, and permissions and governance. And they bring the product intuition to connect all of it to real outcomes. In healthcare, the stakes are higher still — AI systems must function amid messy real-world data, domain-specific definitions, privacy constraints, and high-stakes clinical and commercial decisions. Trustworthiness isn't a nice-to-have. It's the product.
Mission of the Role:
As a Full-Stack AI Engineer, you will design and deploy end-to-end AI solutions that power real products and internal tools. You'll work at the intersection of applied research, engineering, and product development — bringing modern AI techniques into scalable production systems.
You'll operate in a lean, high-leverage pod: a small team of Full-Stack AI Engineers paired closely with a PM who deeply understands the customer workflow — built to compress the discovery loop and ship things that actually matter. You'll also collaborate with platform and data teams to build AI capabilities that transform how healthcare data is explored, understood, and operationalized.
Looking back on your first 12 months at Komodo Health, you will have accomplished…
- Shipped production AI features that improve the precision, usability, and intelligence of Komodo's platform.
- Designed and deployed agent-based AI pipelines integrated into real customer-facing products.
- Built internal AI productivity tools that accelerate engineering workflows across Komodo.
- Prototyped and validated new AI approaches using emerging research and model capabilities.
- Contributed reusable prompt templates, orchestration patterns, and AI system architecture.
- Implemented monitoring, evaluation, and observability frameworks for deployed AI services.
What You'll Own:
- Designing, building, and deploying end-to-end AI systems across the full intelligence stack — from data context and retrieval to agent orchestration, evals, versioning, and governance.
- Developing agent pipelines, prompt chains, and orchestration frameworks for LLM-driven workflows.
- Selecting the right AI technique (LLMs, classic ML, or hybrid approaches) for the problem at hand.
- Collaborating with PMs, engineers, and data scientists to define requirements and deliver solutions.
- Building scalable AI services with monitoring, evaluation, and deployment pipelines.
- Contributing reusable patterns to Komodo's AI infrastructure and internal tooling ecosystem.
What you bring to Komodo Health (required):
- Experience building production-grade AI systems or AI-powered applications.
- Strong proficiency in Python.
- Experience working with LLMs, prompt engineering, or agent-based architectures.
- Familiarity with modern GenAI tooling and frameworks: vLLM, CrewAI, Strands, OpenAI / Chat Completions APIs.
- Ability to integrate AI capabilities across backend services and product interfaces.
- Experience designing evaluation frameworks, testing strategies, or monitoring systems for AI features.
- Strong collaboration skills across engineering, product, and data teams.
Expectations of AI Use in this role (required):
- At Komodo, AI is core to how we build. Full-Stack AI Engineers are expected to actively experiment with new AI techniques, share learnings across teams, and contribute to evolving best practices for building reliable, scalable AI systems. You will play a key role in shaping Komodo's AI-first engineering culture.
Additional skills and experience we’d prioritize (nice to have)…
- Healthcare data expertise.
- Experience with distributed computing frameworks (e.g., Spark, Snowflake, Databricks) for large-scale data processing.
*Compensation bands are inclusive of two levels
**Location flexible: NYC or SF hybrid, or remote
***Of note, this role will remain posted until July 17, so we have time to review applications thoughtfully. Once all current resumes have been reviewed, the role will be reposted as needed.