The Applied AI Engineering team helps developers and enterprises deploy generative AI safely and effectively. We serve as trusted technical advisors, helping customers and partners move from early experimentation to production-scale AI systems.
As a Partner Applied AI Engineer focused on Google Cloud, you will help customers build with OpenAI in the cloud environment they already use. You will work with Google Cloud and its partner ecosystem to turn early implementations into repeatable approaches that field teams can deliver independently.
We are looking for an experienced technical leader to serve as a primary technical counterpart to Google Cloud Customer Engineers, AI specialists, and partner technical teams.
You will shape joint technical strategy, define engagement models, and build systems that scale beyond individual deals. Working across pre- and post-sales, you will guide enterprise customers from discovery through production while enabling Google Cloud and its partners to lead subsequent deployments.
This role combines hands-on engineering, technical judgment, and ecosystem leadership. You will bring deep familiarity with Gemini Enterprise Agent Platform (formerly Vertex AI), particularly Model Garden and its Python SDK tooling, and help customers choose supported OpenAI integration paths based on workload requirements, model capabilities, security controls, and operational needs.
In this role, you will:
Strategic Google Cloud engagement and influence
Build trusted relationships with Google Cloud field leadership, Customer Engineers, AI specialists, and partner teams across regions.
Influence joint account strategy and identify new opportunities where OpenAI can improve customer outcomes within Google Cloud environments.
Define engagement models and prioritization frameworks that concentrate technical effort on high-impact opportunities and reusable solutions.
Help teams distinguish model access through Model Garden, purchasing through Google Cloud Marketplace, and direct OpenAI offerings.
Complex deal leadership and execution
Lead technical strategy for complex enterprise engagements, from use-case discovery and architecture design to prototyping, evaluation, and production deployment.
Resolve integration and operational blockers with OpenAI and Google Cloud counterparts, giving account teams clear decisions and next steps.
Validate model and feature availability, regional requirements, access controls, data handling, quotas, and support boundaries for each workload.
Prioritize opportunities and allocate technical resources according to customer impact and the potential to scale through the ecosystem.
Solution architecture and hands-on building
Design and build OpenAI-powered applications that integrate with Google Cloud services, including Cloud Run or Google Kubernetes Engine, Cloud Storage, and BigQuery where appropriate.
Develop reference implementations for supported Model Garden access to OpenAI through the Responses API, alongside direct OpenAI integration patterns where those better meet customer requirements.
Use the Vertex AI SDK for Python / Agent Platform SDK to discover deployable Model Garden models, inspect deployment configurations, and deploy supported open models to endpoints. Validate project, region, machine and accelerator choices, credentials, permissions, and test inference; distinguish this workflow from managed model API access.
Maintain supported SDK dependencies and adapt examples as Google updates its SDKs. Use Google Gen AI SDK for Google generative-AI capabilities migrated out of legacy Vertex AI modules, and the documented OpenAI API or SDK for OpenAI integration paths.
Build retrieval-augmented generation and tool-using workflows, connecting approved enterprise data and services with clear authorization boundaries.
Establish evaluation, observability, CI/CD, and operational practices that address output quality, safety, reliability, latency, and cost.
Make identity, networking, secrets management, and data governance explicit in architectures rather than assuming controls transfer between services or providers.
Ecosystem enablement and scale
Create workshops, demos, playbooks, and reference architectures that Google Cloud teams and systems integrators can use independently.
Teach partner engineers how to evaluate model choices in Model Garden and select deployment approaches based on customer needs.
Pair with field teams on early deployments, then transfer delivery ownership as patterns mature.
Scale through global and regional systems integrators and independent software vendors, maintaining reusable assets as integrations evolve.
Cross-functional leadership and feedback
Work with Alliances, Product, Engineering, GTM, and Enablement to align technical priorities and execution.
Turn recurring customer and partner issues into evidence-backed product feedback and specific requests.
Maintain clear guidance on validated capabilities, preview limitations, and unresolved gaps, and follow decisions back to the field.
You'll thrive in this role if you:
Have substantial technical consulting or equivalent experience, including relationships with senior technical and business leaders in complex organizations.
Have hands-on experience with Model Garden and the Vertex AI SDK for Python / Agent Platform SDK, including programmatic model discovery, deployment configuration, endpoint deployment, and inference testing. Understand how this tooling differs from Google Gen AI SDK and OpenAI API/SDK integration paths.
Can build production applications using Python or another relevant language, APIs, containers, and cloud services.
Have practical experience with LLM evaluation, retrieval, tool use, and secure enterprise integration.
Balance hands-on delivery with strategic influence, know when to go deep and when to enable others, and build trust with engineers, architects, and executives.
Prefer repeatable solutions, take ownership of ambiguous problems, and measure success through customer outcomes and partner self-sufficiency.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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