Manager, Partner Applied AI Engineering (AWS)

ABOUT THE TEAM

The Applied AI Engineering (AAE) team is responsible for helping developers and enterprises turn the potential of generative AI into real-world impact. We act as trusted advisors and technical partners to customers and ecosystem partners, helping identify high-impact AI use cases and bring them into production through strong architectural guidance and hands-on execution.

The Partner Applied AI Engineering organization works closely with strategic cloud providers, systems integrators, consultancies, and implementation partners to scale successful adoption of OpenAI technologies. As the leader of the AWS Partner AAE pod, you will manage a team of Applied AI Engineers focused on enabling AWS-aligned partners and their customers to build, deploy, and operationalize AI applications on OpenAI’s platform.

ABOUT THE ROLE

We are seeking a Manager, Partner Applied AI Engineering – AWS to lead a team of Applied AI Engineers supporting strategic AWS ecosystem partnerships. In this role, you will own the technical success strategy for AWS-aligned partners and help build scalable, repeatable ways for partners and their customers to adopt OpenAI technologies.

Your team will guide partners and customers across the full AI implementation lifecycle—from identifying and shaping high-value use cases to solution design, architecture, production deployment, optimization, and adoption growth. You will work cross-functionally with internal and external stakeholders across Sales, Partnerships, Product, Research, and Engineering to ensure the voice of partners and customers informs our platform roadmap and how we bring OpenAI technology into production at scale.

This role requires a blend of technical depth, customer leadership, operational rigor, and people management. Success will be measured through production deployments, partner technical maturity, API adoption growth, team development, and the overall impact of the AWS partner ecosystem.

This role is based in our San Francisco office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

IN THIS ROLE, YOU WILL:

- Lead, mentor, and grow a team of Applied AI Engineers supporting strategic AWS partner engagements and customer deployments.

- Define the operating model, engagement strategy, and technical priorities for the AWS Partner AAE pod.

- Partner closely with AWS partner leadership, solution architects, delivery organizations, and customer stakeholders to identify high-impact AI opportunities and accelerate production adoption of OpenAI technologies.

- Guide teams through complex generative AI and traditional ML implementations, including use case shaping, architecture reviews, implementation planning, security considerations, evaluation strategies, and operational readiness.

- Serve as a senior technical escalation point for critical partner and customer engagements, helping teams navigate ambiguity, make sound technical decisions, and drive successful outcomes.

- Collaborate with Product, Research, and Engineering teams to synthesize partner and customer feedback into platform improvements, tooling enhancements, and applied AI best practices.

- Develop scalable enablement frameworks, reference architectures, and repeatable implementation patterns that improve partner effectiveness and reduce time-to-production.

- Drive operational excellence across the team, including resource planning, prioritization, hiring, onboarding, performance management, and career development.

- Act as an external thought leader on applied AI, cloud-native AI architectures, and responsible AI adoption within the AWS ecosystem.

YOU MIGHT THRIVE IN THIS ROLE IF YOU:

- Have 8+ years of experience in technical customer-facing roles, including managing executive-level technical and business relationships with enterprise organizations and strategic partners.

- Have 3+ years of experience leading high-performing technical teams in applied AI engineering, solutions engineering, deployment engineering, forward-deployed engineering, customer engineering, or post-sales environments.

- Have hands-on experience building and deploying generative AI and traditional ML systems in production environments, including familiarity with LLM application architectures, evaluation methodologies, orchestration frameworks, and operational best practices.

- Have strong knowledge of AWS cloud infrastructure and modern cloud-native architectures, including networking, security, compute, storage, observability, and application deployment patterns.

- Have experience working with cloud ecosystem partners, systems integrators, consultancies, or technical alliance organizations.

- Have technical depth in software engineering or solution development using languages such as Python, JavaScript, or TypeScript.

- Are comfortable balancing strategic leadership with hands-on technical engagement and operational execution.

- Are an effective communicator who can translate complex technical concepts into clear business outcomes for executives, partners, developers, and customers alike.

- Have a strong sense of ownership, humility, and curiosity, with a willingness to learn quickly and help others succeed in ambiguous, fast-moving environments.