Join Notable as a Senior AI Platform Engineer to design and maintain LLM integrations that enhance healthcare AI solutions.
Posted by employer 4 months ago
First seen on Joblaze 1 month ago
Last verified on the company career page 17 hours ago
Skills & Technologies
AI in the day-to-day
Leverage AI agents to increase day-to-day efficiency and share learnings that raise the overall quality bar across the engineering environment.
Not disclosed in this posting: compensation, years of experience, visa sponsorship.
Joblaze summary
In the role of Senior AI Platform Engineer at Notable, the individual will focus on designing and maintaining large language model (LLM) integrations that enhance AI functionalities across healthcare solutions. Key skills include strong Python proficiency and experience with Jupyter Notebook, alongside a solid understanding of building scalable and reliable production systems. This position is ideal for someone with a background in AI services and a knack for translating complex problems into actionable technical plans. Notable emphasizes a collaborative culture aimed at transforming healthcare through innovative technology.
Joblaze insights
Quick facts
- Is the AI Platform Engineer role remote?
- It's hybrid — Notable expects some on-site time in San Mateo, CA.
- Where is the role based?
- Notable is hiring for this position in San Mateo, CA.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Google Cloud Platform, Helm Charts, Jupyter Notebook, LLM, PostgreSQL, Python.
- What seniority level is this role?
- Notable targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this AI Platform Engineer role at Notable.
From the original posting
Role Summary:
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.
You’re a Great Fit if:
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.
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Standard company text repeated across Notable's postings is omitted here.