GenAI Sales Manager
Amazon Web Services•Published 1 days ago•First seen 1 days ago
Amazon Web Services (AWS) is leading the next phase of AI adoption with GenAI and Agentic AI technologies and is seeking a senior, technically strong leader who can translate AI capability into real customer outcomes.
This role sits at the intersection of deep AI understanding, industry context, and execution. You will work hands-on with customers to qualify AI use cases, shape AI solutions, and ensure initiatives move from intent to deployable, production-ready systems. Success in this role depends on technical credibility, delivery discipline, and the ability to guide customers through real architectural and operating trade-offs in AI systems.
AWS Global Sales enables customers of all sizes to innovate and scale on the AWS cloud. As organizations across ASEAN move from experimentation to production with foundation models, LLMs, and agentic systems, this role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments.
This is a quota-carrying role, with revenue targets used as a measure of delivery impact. Quota credit is aligned to AI opportunities that reach production-ready scope, reinforcing accountability for feasibility, cost, and execution quality rather than intent or pilots.
Key job responsibilities
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
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 conferences, inspire us to never stop embracing our uniqueness.
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 in the cloud.
This role sits at the intersection of deep AI understanding, industry context, and execution. You will work hands-on with customers to qualify AI use cases, shape AI solutions, and ensure initiatives move from intent to deployable, production-ready systems. Success in this role depends on technical credibility, delivery discipline, and the ability to guide customers through real architectural and operating trade-offs in AI systems.
AWS Global Sales enables customers of all sizes to innovate and scale on the AWS cloud. As organizations across ASEAN move from experimentation to production with foundation models, LLMs, and agentic systems, this role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments.
This is a quota-carrying role, with revenue targets used as a measure of delivery impact. Quota credit is aligned to AI opportunities that reach production-ready scope, reinforcing accountability for feasibility, cost, and execution quality rather than intent or pilots.
Key job responsibilities
- Originate, qualify, and own GenAI and Agentic AI opportunities end-to-end to production with account teams, regional sales, industry teams and specialists; Own/exceed GenAI/Agentic AI revenue targets; maintain accurate qualification and forecasting; build annual/territory plans to maximise revenue growth
- Translate customer business objectives into scalable, secure, and operable AI architectures across data pipelines, foundation models, RAG, agentic patterns, deployment, and operations
- Act as technical authority by advising customers on AI maturity, operating models, responsible AI, cost drivers, risk, model selection, fine tuning, and production trade-offs; build differentiate value for AWS.
- Lead executive workshops, technical discovery, and complex multi-stakeholder AI engagements, balancing value, feasibility, cost, and delivery risk
- Define relevant AI POVs with explicit success criteria, timelines, cost envelopes, and clear production paths to differentiate AWS; collaborate with AI Solution architects and engineering teams to execute, drive engagement progress towards closure
- Ensure AI solutions meet security, regulatory, reliability, cost, and operability requirements before production sign-off
- Govern partner and SI-led GenAI and Agentic AI implementations through architecture standards, technical reviews, and acceptance criteria
- Build internal AI field capability by creating technical content, best-practice guidance, and reusable reference architectures, patterns and customer learnings, and feed structured feedback into AI product roadmaps.
- Engage with AWS AI product teams to drive successful customer outcomes, provide feedback, influence roadmaps to ASEAN needs.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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
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 conferences, inspire us to never stop embracing our uniqueness.
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 in the cloud.
Basic Qualifications
- 7+ years of experience in technology roles delivering or supporting AI, ML, or data-driven systems in customer-facing environments, with a proven track record of technical sales and demonstrated work on complex, multi-stakeholder AI sales engagements involving long sales and delivery cycles.
- Experience shaping, influencing, and closing AI- and data-led programs, with the ability to translate AI technical concepts into clear business implications for both technical and executive audiences.
- Strong understanding of GenAI concepts and AI architectures, including foundation models, LLMs, agent-based systems, and RAG patterns, as well as AI system design considerations such as AI data pipelines, model lifecycle, deployment, and operations.
- Deep knowledge of AI cost drivers and AI unit economics, including inference costs, scale trade-offs, and operating considerations, supported by working knowledge of AWS AI/ML services such as Amazon Bedrock, SageMaker, or equivalent.
- Bachelor’s degree in Computer Science, Engineering, or a related field with a focus on AI, ML, or data systems.
Preferred Qualifications
- Hands-on experience building, integrating, or operating GenAI and ML systems in production and advanced POV environments, with practical use of AI/ML frameworks such as PyTorch, TensorFlow, LangChain, LlamaIndex, or equivalent.
- Hands-on exposure to prompt engineering, RAG implementation, fine-tuning approaches, and AI model evaluation techniques, applied to real-world or near-production AI solutions.
- Experience deploying or governing AI systems in production or regulated environments, with a background in solution architecture, engineering, or consulting roles involving AI system delivery.
- Familiarity with responsible AI practices, governance frameworks, and model risk considerations when designing, deploying, or overseeing AI solutions.
- Advanced degree (MS/PhD) in AI, ML, Computer Science, or related fields, providing strong theoretical and practical foundations for AI system development and delivery.