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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