Partner Applied AI Engineer, Oracle and Cloud ISV

About the team

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.

About the role

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.

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.
• Snowflake: Work with Snowflake account and technical teams to qualify data and AI workloads where OpenAI models in Snowflake Cortex AI are a fit.
• 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.

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.

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.

You'll thrive in this role if you:

• 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.