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Open nowPosted 30 days ago

APJ Partner Category Lead - Frontier Models

MyCareersFuture94,028 open roles

Pay
SGD 13,000 – SGD 24,000 a Monthly
Where
Central, Singapore
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Your applicationOpen nowAPJ Partner Category Lead - Frontier ModelsMyCareersFuture · Central, Singapore
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This job: posted 30 days ago

The posting

As the APJ Frontier Models Category Lead, you will own and drive the end-to-end AWS and Frontier Model provider partnership strategy across the Asia-Pacific and Japan region. You will be responsible for understanding customer and market signals, accelerating customer adoption of Frontier models on AWS, growing top-line revenue growth and overall end customer adoption across all market segments and across all countries in APJ. This is a high-visibility, high-impact role that sits at the intersection of AWS's largest AI partnerships and our fastest-growing customer workloads. You will serve as the single-threaded owner (STO) for the Frontier Model partnership in APJ orchestrating executive governance, field enablement, go-to-market execution, and competitive positioning.

The ideal candidate will have direct sales and/or ISV/Technology Partner experience, as well as deep familiarity with the AI/ML landscape, cloud platform economics, and enterprise partner development. The candidate will have strong business acumen and problem-solving skills, as well as the ability to manage multiple customer personas and successfully align executive stakeholders with differing goals. A strong executive presence and the ability to successfully manage ambiguous, fast-moving situations autonomously and deliver results is required.

Key job responsibilities

  • Define and execute the APJ partnership strategy, goals and metrics. Break down the overall goals and metrics into country/area outcomes
  • Set up partner governance and executive engagement. Establish and run partnership operating model, serve as AWS's primary relationship holder with partner's APJ leadership.
  • Build scalable enablement across APJ including country-level working groups, partner launch events, and field training.
  • Work with cross-functional stakeholders (AI/ML Specialists, Partner Leaders, Sales Leaders) to deliver integrated campaigns and customer engagements
  • Enable Area/Country Partner teams to serve as local representatives for the partnership - delivering comprehensive onboarding, weekly office hours, and monthly enablement sessions
  • Work back from market signals to identify and mitigate partnership risks (capacity constraints, policy issues, feature availability) with proactive remediation plans
  • Track and communicate key metrics: ARR, TCV, pipeline coverage. Maintain pipeline visibility and reporting cadence.

A day in the life Your day might start with a pipeline review call with Japan's Area Partner team to unblock a strategic enterprise deal, followed by a bi-weekly sync with APJ partner leadership to align on upcoming product launches. Mid-morning you're reviewing market signals and customer feedback. After lunch you're enabling a group of sellers on a new co-sell play, and in the afternoon you're leading an executive monthly business review presenting APJ progress to world wide leadership.

About the team The APJ Partner Category Team is responsible for AWS's most strategic technology partnerships across Asia-Pacific and Japan. We operate as category leaders - each owning an end-to-end partnership strategy that spans revenue, GTM, enablement, and executive governance. We work at the intersection of AWS's fastest-growing services and our partners' go-to-market ambitions to drive customer outcomes at scale.

Diverse Experiences Amazon 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.

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.

Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship and 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.

Basic qualifications

  • 3+ years of business development, partnership management, or sourcing new business experience
  • Bachelor's degree or equivalent
  • Experience using data and metrics to determine and drive improvements
  • Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
  • 5+ years of communicating with and presenting to executive and senior audiences experience

Preferred qualifications

  • • 5+ years of experience in technology partner development, ISV alliances, or strategic business development in the cloud/AI ecosystem
  • • Direct experience managing frontier AI model or platform partnerships
  • • Demonstrated ability to drive $100M+ revenue targets through partner co-sell motions
  • • Track record of building operating models, governance mechanisms, and field enablement at scale
  • • Understanding of AI/ML infrastructure economics (GPU capacity, inferencing costs, model deployment architectures)
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