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San Francisco, California, United States
Onsite
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 Cloud ISVs, you will work with Oracle Cloud, Snowflake, and Databricks to help customers adopt OpenAI. You will bring OpenAI capabilities to the applications, data platforms, and developer workflows customers already use, then turn successful deployments into approaches the field and partner teams can deliver independently.
We are looking for an experienced technical leader to work with partner architects, AI specialists, and sales teams across three distinct routes to market. You will lead technical work from joint account discovery and architecture through evaluation and production, alongside OpenAI account teams and partner sellers. You will help customers choose the right deployment and purchasing path for the workload, with clear ownership of security, billing, support, and operations.
Strategic partner engagement and influence
Build relationships with Oracle, Snowflake, and Databricks field leaders and technical teams. Shape joint account plans, identify the customer problem each partner can help solve, and prioritize opportunities with a clear path to production and reuse.
Oracle Cloud: Work with Oracle sellers on eligible, sales-managed Oracle Marketplace private offers for OpenAI API models, ChatGPT Work, and Codex. Distinguish procurement, billing, and eligible commitment drawdown from OpenAI-managed product access, inference, and support. Where customers build on OCI, design the application and data integration without assuming the model is hosted on OCI.
Snowflake: Work with Snowflake account and technical teams to qualify data and AI workloads where OpenAI models in Snowflake Cortex AI are a fit. Help customers evaluate use cases such as AI functions over governed data, search, analytics, and agents. Confirm model and regional availability, data boundaries, and operating requirements. Distinguish Snowflake-metered Cortex usage from a customer application that calls OpenAI directly.
Databricks: Work with Databricks sellers and solution architects on three joint plays: developer workflows with Codex and Unity AI Gateway, enterprise insights with ChatGPT and Genie where supported, and GPT-powered applications and agents with Mosaic AI Model Serving, Agent Bricks, and Databricks Apps. Validate each route against the customer’s governance and deployment requirements. Distinguish Databricks-billed usage from direct OpenAI billing and confirm commercial eligibility and attribution before making commitments.
Complex deal leadership and execution
Lead technical discovery, architecture, prototyping, evaluation, and production readiness. Agree with both account teams on what the customer will deploy, how success will be verified, and who owns the next step.
Validate model and feature availability, identity and network boundaries, data handling and residency, capacity, metering, and support ownership. Work with Alliances, Sales, and Billing Ops on technical readiness without taking ownership of pricing, terms, offer acceptance, or billing approvals.
Solution architecture and hands-on building
Build reference implementations with OpenAI APIs and partner-native capabilities, such as OCI application and data services, Snowflake Cortex AI, and Databricks Mosaic AI Model Serving. Use the appropriate integration path for the workload and validate permissions and data movement before deployment.
Put evaluation, observability, and deployment practices in place to measure quality, safety, reliability, latency, cost, and real workload usage.
Ecosystem enablement and scale
Create demos, workshops, reference architectures, and playbooks that partner engineers, field teams, and systems integrators can use independently. Pair on early deployments, then hand off proven patterns with clear prerequisites and support paths.
Cross-functional leadership and feedback
Work with Alliances, Sales, Product, Engineering, and Enablement to resolve blockers. Turn patterns across accounts into specific product feedback backed by evidence, and keep field guidance current on what is supported, what is limited, and what is not yet available.
Have substantial experience leading technical engagements with enterprise engineering and business leaders across pre- and post-sales.
Have hands-on depth in at least one of OCI, Snowflake, or Databricks and can build credible architectures across the others. You understand enterprise data governance and know how to integrate OpenAI products into production systems.
Can build in Python or a comparable language and have practical experience with APIs, retrieval, tool use, LLM evaluation, and secure cloud deployments.
Can explain how a workload is purchased, accessed, served, metered, and supported without conflating those decisions. You build trust across sales and engineering, and measure success through customer adoption 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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