Partner Applied AI Engineer (Google Cloud)

Quick Facts

• Partner-facing technical leadership role focused on deploying OpenAI-powered solutions on Google Cloud.
• Hands-on engineering plus ecosystem enablement to make deployments repeatable.

Description

As a Partner Applied AI Engineer focused on Google Cloud, you help customers build with OpenAI in the cloud environment they already use. You lead technical strategy and complex enterprise engagements from discovery through production, using Gemini Enterprise Agent Platform (formerly Vertex AI)—particularly Model Garden and its Python SDK tooling—to define scalable, secure deployment patterns. You also create reference architectures, workshops, and playbooks so partner teams and customer field teams can deliver independently.

Responsibilities

• Shape joint technical strategy and define engagement models to concentrate effort on high-impact, reusable opportunities.
• Lead complex deals: architecture design, prototyping, evaluation, and production deployment.
• Resolve OpenAI and Google Cloud integration and operational blockers with clear next steps.
• Validate model/feature availability, regional needs, access controls, data handling, quotas, and support boundaries.
• Design and build OpenAI-powered applications integrating with Cloud Run or Google Kubernetes Engine, Cloud Storage, and BigQuery.
• Create reference implementations for Model Garden access via the Responses API, alongside direct OpenAI integration patterns.
• Use Vertex AI SDK for Python / Agent Platform SDK to discover deployable Model Garden models, inspect deployment configurations, and deploy supported open models to endpoints (including credentials and permission validation and inference testing).
• Maintain supported SDK dependencies and adapt examples as Google updates its SDKs.
• Build retrieval-augmented generation and tool-using workflows with clear authorization boundaries.
• Establish evaluation, observability, CI/CD, and operational practices covering output quality, safety, reliability, latency, and cost.
• Make identity, networking, secrets management, and data governance explicit in architectures.
• Enable partners through workshops, demos, playbooks, and reference architectures; teach model evaluation and deployment approach selection.
• Coordinate with Alliances, Product, Engineering, GTM, and Enablement; turn recurring issues into evidence-backed product feedback.

Benefits

• Equal opportunity employer; background checks administered in accordance with applicable law.
• Reasonable accommodations available for applicants with disabilities.