GenAI Solutions Architect Manager
Amazon Web Services•Published 1 days ago•First seen 1 days ago
Amazon Web Services (AWS) is at the forefront of the GenAI and Agentic AI revolution, empowering organizations to redefine what is possible through intelligent automation. We are seeking a strategic, hands-on Solutions Architect (SA) Manager to lead and scale a world-class team of architects dedicated to designing and building production-grade AI systems for our customers.
This is a high ownership, hands on player-coach role where the manager is a recognised AI expert, remains directly involved in customer engagements, designing, building and reviewing production AI systems. You will be the “connective tissue” between customers, sales, Go-To-Market, AWS service teams teams to ensure our AI technical strategy drives innovation, measurable business outcomes and long-term customer success.
As organizations across ASEAN move from experimentation to enterprise-grade production with foundation models and autonomous agentic systems, this role focuses on building AI talent and the frameworks necessary to convert AI ambition into scalable, secure, and resilient programs. You will mentor a team that masters everything from full-stack development and AgentOps to model fine-tuning and responsible AI governance, ensuring that every solution is optimized for performance, cost, and compliance.
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 is a high ownership, hands on player-coach role where the manager is a recognised AI expert, remains directly involved in customer engagements, designing, building and reviewing production AI systems. You will be the “connective tissue” between customers, sales, Go-To-Market, AWS service teams teams to ensure our AI technical strategy drives innovation, measurable business outcomes and long-term customer success.
As organizations across ASEAN move from experimentation to enterprise-grade production with foundation models and autonomous agentic systems, this role focuses on building AI talent and the frameworks necessary to convert AI ambition into scalable, secure, and resilient programs. You will mentor a team that masters everything from full-stack development and AgentOps to model fine-tuning and responsible AI governance, ensuring that every solution is optimized for performance, cost, and compliance.
Key job responsibilities
- Set the AI Technical Bar through Strategic Customer Engagements: Act as the AI technical executive sponsor for strategic accounts, leading discussions with C-suite/AI leaders and drive conversations around AI architecture, solution design, capability roadmaps, organizational readiness, and operational risk.
- Build & Scale a High-Performance AI tech team: Recruit/develop a world-class team of hands-on full stack AI Solutions Architects, establishing a culture of AI technical excellence and customer obsession.
- Talent Mentorship & Growth of AI SA’s: Provide deep technical mentorship in AI such as: model serving trade-offs (latency, cost, quality), agent orchestration, state management, evaluation, and vector database design at scale. Mentorship must be grounded in hands-on knowledge.
- Strategic AI Engagements: Partner closely with Sales and Go-To-Market leadership to define technical qualification criteria for AI/ML opportunities. Ensure AI deals are rooted in clear production paths, unit economics, and operational feasibility, not experimentation alone. Sell AI architectural outcomes and long-term platforms, rather than isolated features or proofs of concept.
- Resource & Capacity Planning: Be Single Threaded Owner (STO) of all AI infrastructure and service related requirements of customers and work closely with service teams. Ensure allocation of SA resources across accounts and territories, prioritizing high-impact, production-bound AI initiatives. Continuously assess skill coverage to ensure the team can support advanced AI workloads.
- Bridge Field Insights to Product: Serve as the primary technical advocate for customer needs within AWS, translating real-world production blockers into actionable feedback for service teams. Provide structured insights on where AI services succeed or fail at scale, influencing roadmap prioritization and feature development. Represent ASEAN customer realities in global product discussions with credibility and technical depth.
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
- 10+ years of managing a technical team of solution architects, sales engineers or similar technical roles experience
- Ability to lead executive discussions, including whiteboarding full AI system architectures, explaining failure modes, cost structures, and trade-offs to C-suite stakeholders.
- 4+ years directly managing AI Solutions Architects or Staff/Principal Engineers responsible for design, development, and deployment of AI systems, including traditional machine learning, modern generative or agentic AI systems.
- Demonstrated ability to architect AI systems from first principles, including model selection and fine-tuning strategy, inference topology and scaling model, data retrieval, and evaluation design, and modern agentic frameworks like Strands, LangGraph.
- Hands-on experience operating AI workloads on AWS or any other cloud providers used beyond pilots in secured & governed enterprise environments.
Preferred Qualifications
- Experience architecting, migrating, transforming or modernizing customer requirements to the cloud
- Master's degree or equivalent in computer science, machine learning, engineering, or related fields, or PhD
- Experience in leading large-scale, technical or engineering programs with a proven record of thought leadership, business case development, realizing customer benefits, and successful program completion
- Deep familiarity with AI economics including cost-per-inference modeling, trade-offs between managed services and self-hosted infrastructure, optimization strategies such as batching, quantization, or model tiering.
- Recognized technical credibility demonstrated by original contributions, such as published technical articles with real architectural depth, conference talks focused on production AI lessons, open-source contributions to AI infrastructure, tooling, or evaluation frameworks.