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# AI Platform Engineer

- **Company:** NOTABLE, INC.
- **Location:** San Mateo, CA, United States
- **Experience:** Expert
- **Salary:** $170,000.0 - $205,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Storage, Python (Programming Language), PostgreSQL, Application Data, Systems Integration, TypeScript, Jupyter Notebook, Google Cloud, Large Language Models, Kubernetes Helm Charts, AI Platforms, Kubernetes, Terraform, Databricks
- **Published:** June 14, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=a47ade5c776efebe

## About the Role

Do you have experience in UI?, * Strong proficiency in Python for production software.

 * Proficiency with Jupyter Notebook or an equivalent environment (e.g., JupyterLab, Databricks, Colab, etc.).
 * Demonstrated experience building, integrating, and operating LLM-powered features/services.
 * Ability to decompose ambiguous problems, write clear technical plans, and execute with high ownership.
 * Experience designing for reliability, scalability, and observability in production systems.
 * You leverage AI Agents for day-to-day efficiency.

Nice to Have:

 * Terraform and Helm Charts for infrastructure and deployment.
 * Google Cloud Platform (e.g., GKE, Cloud Run, Cloud Storage).
 * Typescript for service or UI integrations.
 * Postgres for application data modeling and performance.
 * Experience with ML/AI platforms, agents, or orchestration frameworks.

## Description

Notable builds AI-driven automation for healthcare. As a Senior AI Platform Engineer, you will design, build, and maintain LLM integrations that power AI features across Notable's solutions. You'll translate ambiguous problem statements into clear, high-quality technical plans and own delivery end-to-end - from ideation and requirements, to implementation, launch, and post-delivery monitoring - with a focus on scalability, reliability, and measurable impact for our customers. You'll also leverage AI agents to increase day-to-day efficiency and share learnings that raise the overall quality bar across the engineering environment.

What You'll Do:

 * Develop and maintain LLM integrations to power AI features across solutions.
 * Ensure scalability, reliability, and performance of AI features in production.
 * Translate abstract requirements into structured, sound technical plans and milestones.
 * Own implementations end-to-end: discovery/requirements design build launch post-delivery monitoring/iterating.
 * Evaluate and articulate implications and trade-offs of technical choices.
 * Leverage AI agents to improve development velocity and operational efficiency.
 * Collaborate across engineering and adjacent teams to share learnings, improve processes, and continuously raise quality.


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