AI Platform Engineer

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.

#LI-TD1

We value in-person collaboration and connection. For Bay Area–based employees, this role requires being in our San Mateo office at least three days a week. For remote employees, occasional travel to headquarters is expected for company-wide events and onsite gatherings.

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