Manager, Partner Applied AI Engineering

About the role

You will lead the technical strategy and execution for AWS-aligned partners within the Applied AI Engineering organization, shaping how enterprise customers adopt OpenAI technologies through the AWS ecosystem. You own the end-to-end success of partner engagements, from initial use case discovery through architecture design, production deployment, and long-term optimization. This position requires you to act as both a hands-on technical leader and a strategic advisor, guiding complex generative AI implementations with rigorous evaluation and operational discipline. You will mentor engineers, define engagement patterns, and ensure that solutions are scalable, secure, and aligned with platform best practices. Success in this role will be defined by your ability to drive measurable adoption, deepen partner technical maturity, and expand API usage across key accounts. You will synthesize customer feedback into product and platform improvements, ensuring that real-world deployment challenges directly influence OpenAI's roadmap. This is a leadership role that blends architecture, people management, and external engagement to make the AWS partner ecosystem a flagship channel for OpenAI technology.

Key facts

What you'll do

Define and lead the technical operating model for the AWS Partner AAE pod, establishing clear engagement strategies, priorities, and delivery frameworks for partner teams.

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

Lead, mentor, and grow a team of Applied AI Engineers, providing technical guidance, career development, and performance management focused on AWS partner engagements.

Guide partners and customers through the full AI implementation lifecycle, including use case shaping, architecture reviews, implementation planning, security considerations, evaluation strategies, and operational readiness.

Serve as a senior technical escalation point for complex partner and customer engagements, navigating ambiguity and driving sound technical decisions that lead to successful production deployments.

Collaborate with Product, Research, and Engineering teams to translate 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 across the AWS ecosystem.

Drive operational excellence within the team, including resource planning, prioritization, hiring, onboarding, performance management, and structured career development for engineers.

Build and maintain strong relationships with cloud ecosystem partners, systems integrators, consultancies, and technical alliance organizations to expand OpenAI adoption.

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

Evaluate and refine deployment pipelines, evaluation methodologies, and orchestration frameworks to ensure robust, scalable, and secure LLM application implementations.

Support the design and delivery of training and enablement programs that elevate partner technical capabilities and confidence in delivering OpenAI solutions.

Champion data-driven decision making by tracking adoption metrics, deployment success, and partner performance to continuously improve engagement strategies.

Ensure all technical guidance and architectural recommendations align with OpenAI platform capabilities, security standards, and operational best practices.

Requirements

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

You must 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.

You must 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.

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

You must have experience working with cloud ecosystem partners, systems integrators, consultancies, or technical alliance organizations.

You must have technical depth in software engineering or solution development using languages such as Python, JavaScript, or TypeScript.

You must be comfortable balancing strategic leadership with hands-on technical engagement and operational execution in a fast-paced, matrixed environment.

You must be able to communicate effectively with both technical and executive stakeholders, translating complex technical concepts into clear, actionable guidance.

Practical notes

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.

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