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NotableNotableSan Mateo, CA

AI Platform Engineer

Design, build, and maintain LLM integrations powering AI features. Own end-to-end delivery from requirements through production monitoring with focus on scalability and reliability.

170k – 205k/yr
Hybrid5+ YOEML Engineering

About the role

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.

Requirements

  • 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.

Skills

PythonLlm IntegrationJupyter NotebookDatabricksTerraformHelmGCPGKECloud RunTypeScriptPostgres

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