Partner Applied AI Engineer

OpenAI

. Build trusted relationships with Google Cloud field leadership, Customer Engineers, AI specialists, and partner teams .

Posted 11/11/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $197,000 - $278,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building OpenAI-powered applications and integrating with Google Cloud services, utilizing the Vertex AI SDK for Python and other relevant technologies. Proven ability to establish technical strategies, manage complex enterprise engagements, and foster relationships with key stakeholders.

Highest-signal resume keywords

OpenAI IntegrationVertex AI SDK For PythonModel Garden AccessCloud Services DeploymentTechnical Consulting Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingModel DiscoveryDeployment ConfigurationInference TestingData GovernanceIdentity ManagementNetworkingSecrets ManagementRetrieval-Augmented GenerationCloud Architecture

Soft Skills

Relationship BuildingInfluencing StrategyCollaborationTeachingProblem Solving

Tools & Technologies

Google CloudCloud RunGoogle Kubernetes EngineCloud StorageBigQueryVertex AI SDKAgent Platform SDKOpenAI APICI/CD PracticesOperational Practices

Industry Keywords

Technical ConsultingEnterprise EngagementsAI SolutionsCloud EnvironmentsIntegration Patterns

Tech Stack

Tools & technologies

BigQueryCloudKubernetesPython

About the role

Key responsibilities & impact

Build trusted relationships with Google Cloud field leadership, Customer Engineers, AI specialists, and partner teams
Influence joint account strategy and identify opportunities for OpenAI within Google Cloud environments
Define engagement models and prioritization frameworks for high-impact, reusable solutions
Distinguish Model Garden access, Google Cloud Marketplace purchasing, and direct OpenAI offerings
Lead technical strategy for complex enterprise engagements from discovery through production deployment
Resolve integration and operational blockers with OpenAI and Google Cloud counterparts
Validate model and feature availability, regional requirements, access controls, data handling, quotas, and support boundaries
Design and build OpenAI-powered applications integrating with Cloud Run, Google Kubernetes Engine, Cloud Storage, and BigQuery
Develop reference implementations for Model Garden access through the Responses API and direct OpenAI integration patterns
Use the Vertex AI SDK for Python / Agent Platform SDK to discover models, configure deployments, deploy endpoints, validate credentials and permissions, and test inference
Maintain SDK dependencies and adapt examples as Google updates its SDKs
Build retrieval-augmented generation and tool-using workflows with authorized enterprise data and services
Establish evaluation, observability, CI/CD, and operational practices for quality, safety, reliability, latency, and cost
Make identity, networking, secrets management, and data governance explicit in architectures
Create workshops, demos, playbooks, and reference architectures for Google Cloud teams and systems integrators
Teach partner engineers to evaluate Model Garden models and deployment approaches
Pair with field teams on early deployments and transfer delivery ownership as patterns mature
Scale through global and regional systems integrators and independent software vendors
Collaborate with Alliances, Product, Engineering, GTM, and Enablement
Turn recurring customer and partner issues into product feedback and requests
Maintain guidance on validated capabilities, preview limitations, unresolved gaps, and field decisions

Requirements

What you’ll need

Substantial technical consulting or equivalent experience
Relationships with senior technical and business leaders in complex organizations
Hands-on experience with Model Garden and the Vertex AI SDK for Python / Agent Platform SDK
Experience with programmatic model discovery, deployment configuration, endpoint deployment, and inference testing
Understanding of differences among Vertex AI SDK, Google Gen AI SDK, and OpenAI API/SDK integration paths
Ability to build production applications using Python or another relevant language, APIs, containers, and cloud services
Practical experience with LLM evaluation, retrieval, tool use, and secure enterprise integration
Experience with identity, networking, secrets management, and data governance in cloud architectures
Ability to work from the San Francisco office three days per week
Must answer whether employment visa sponsorship in the United States is required

Benefits

Comp & perks

Equity
Performance-related bonus(es) for eligible employees
Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts
Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)
401(k) retirement plan with employer match
Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents)
Paid medical and caregiver leave (up to 8 weeks)
Flexible PTO for exempt employees and up to 15 days annually for non-exempt employees
13+ paid company holidays
Multiple paid coordinated company office closures throughout the year
Paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)
Mental health and wellness support
Employer-paid basic life and disability coverage
Annual learning and development stipend
Daily meals in offices, and meal delivery credits as eligible
Relocation support for eligible employees
Charitable donation matching
Wellness stipends
Overtime pay for non-exempt employees, consistent with applicable laws