Principal Technical Program Manager, Applied AI Solutions, Applied AI Solutions Acceleration Solutions Architecture
✨ AI Summary
Amazon is hiring a Principal Technical Program Manager for its Applied AI Solutions team in Seattle, Washington, to lead the development of agentic AI platforms and enablement programs. The role requires deep technical program management expertise to coordinate cross-functional engineering, GTM, and partner initiatives without a specified minimum years of experience. No salary range or remote policy is mentioned.
The Applied AI Acceleration Solutions Architecture (AAA-SA) team is transforming how specialist expertise is delivered at scale across AWS. We are building agentic solutions that operationalize deep domain knowledge — enabling on-demand, consultative guidance that traditionally required engagement across multiple specialist roles. Our mission is to ensure every customer has on-demand access to trusted, specialized knowledge through personalized engagements that accelerate their business outcomes.
We are looking for a Principal Technical Program Manager to own the end-to-end technical program management of our agentic AI platform development, enablement/badging programs, and demo experience initiatives. In this role, you will drive execution across multiple engineering workstreams, coordinate cross-organizationally with Go-to-Market (GTM) teams, Solutions Architects, and service team engineering, and establish the mechanisms that keep this fast-moving, high-ambiguity program on track. You will operate with complete independence, advise VP-level leadership, and bring clarity to significantly complex, cross-functional initiatives at the intersection of AI, customer engagement, and enterprise knowledge management.
This is a strategic role that requires both deep technical program management acumen and the ability to navigate a landscape where the business and architectural strategy is still being defined. You will shape how we measure success, how we communicate progress, and how we scale our solutions from internal specialist teams to AWS field teams, partners, and ultimately customers.
Key job responsibilities
Engineering & Delivery Management
- Agentic AI Platform: Own end-to-end program management for the agentic AI solutions, driving the integrated roadmap and milestones from concept through production across all engineering workstreams.
- Engineering Coordination: Drive engineering coordination across engineering teams that co-develop production-grade AI solutions, and manage sprint cadences, dependency tracking, and releases.
- Risk Management: Proactively identify and mitigate risks across engineering capacity, agentic platform readiness, knowledge accuracy, and change management. Establish escalation paths and drive resolution before blockers materialize.
Business Reviews & Reporting
- Business Reviews: Own and run business reviews with comprehensive metrics on adoption, user satisfaction, knowledge coverage, and engineering velocity. Define the mechanisms that surface the right data to the right audience at the right time. Author monthly business roll-ups for VP-level audiences that synthesize engineering progress, business impact metrics, adoption trends, and strategic recommendations into a compelling narrative.
- Program Flashes: Produce and deliver program flashes providing leadership with crisp, data-driven status updates across all active workstreams — highlighting progress, risks, blockers, and key decisions needed.
Cross-Organizational Coordination
- Multi-org Alignment: Serve as the connective tissue between the Applied AI SA team, dedicated engineering teams, and service team engineering leadership. Align priorities, negotiate resources, and ensure joint accountability across organizations.
- GTM Partnership: Partner with GTM teams, solution architects, sales specialists, and customer success managers to ensure product development is informed by field feedback and aligned to revenue acceleration objectives.
- Ecosystem Integration: Coordinate with broader AWS initiatives (e.g., WWSO agentic programs, enterprise tools) to ensure interoperability, avoid duplication, and maximize the reach of composable knowledge agents.
Enablement & Badging Programs
- Badging Program: Own the program management for AI enablement and badging/certification programs that upskill AWS specialist and field teams. Define learning paths, track completion metrics, and drive adoption targets.
- Knowledge Champion Network: Coordinate the knowledge champion network — ensuring domain experts across specialist roles contribute to and govern AI-ready knowledge assets on a structured cadence.
- Enablement Execution: Manage enablement session planning, asset development tracking, and feedback loop mechanisms that continuously improve solution quality and user satisfaction.
Demo Experience Program
- Demo Development: Coordinate demo development across industry-specific demos, live demo environments, and deployable assets that empower SAs and sellers across all deal stages.
- Platform Evolution: Manage the portal’s transition to next-generation demo infrastructure, including partner onboarding workflows, content publishing processes, and cross-team integration requirements.
A day in the life
You start your morning reviewing adoption metrics and preparing a concise update for a VP-level review on Applied AI Solutions Acceleration program. Mid-morning, you lead a working session with solution architects and engineering leads to align on a technical approach for transforming business outcomes using agentic solutions. After lunch, you partner with go-to-market team members to validate that the solution meets field team needs, then join a design review where you surface hidden risks and push toward a simpler path forward.
About the team
The Applied AI Acceleration Solutions Architecture team sits within Applied AI Solutions and was chartered to address the challenge of scaling specialist expertise to meet customer demand.
Our approach is phased and deliberate: we deploy with specialist teams for rapid testing and learning, expand to broader AWS field teams for scale validation, and ultimately launch to partners and customers as proven solutions. We are customer zero for Applied AI, and the insights we capture at scale directly inform our external customer solutions.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.
About the Company
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