Are you passionate about Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), Generative AI, and Agentic AI? Are you energized by the opportunity to drive production usage of ML and AI at scale? We'd love to hear from you.
ML and AI, especially Generative AI and Agentic AI, are rapidly transforming how we work and live. We're witnessing the impact of Generative AI creating everything from code to content, while Agentic AI systems are autonomously solving complex business challenges. From home automation and mobile apps to financial trading and shipping logistics, AI is reshaping every industry. Given the computational scale required for developing AI models, particularly large language models and autonomous agents, the cloud is an ideal environment for deploying AI models, and Amazon Web Services (AWS) leads this space. We're seeking someone who is passionate about AI's potential to help customers understand how it can transform their businesses.
As an AI/ML Specialist Solutions Architect (SA), you will serve as a Subject Matter Expert for designing scalable, secure, and cost-effective AI/ML, Generative AI, and Agentic AI solutions that leverage AWS services. Working at the intersection of innovation and enterprise requirements, you'll architect production-grade solutions that are reliable, well-governed, and compliant with industry standards. Your expertise will be important in helping organizations build responsible AI practices, from traditional ML to advanced Generative AI and Agentic AI systems, while defining robust governance frameworks and secure AI pipelines that scale efficiently.
As part of the GenAI Specialist Solutions Architecture team for Strategic Accounts, you will guide customers through their AI transformation journey, collaborating closely to establish scalable GenAIOps practices and create sustainable, enterprise-grade AI architectures that deliver measurable business value. Your role involves engaging directly with customers to understand their unique requirements and translating them into robust technical architectures. You'll present AWS services and solutions, develop technical content that captures best practices and proven patterns, and enable customers, partners, and ISVs to fully leverage AI/ML and Generative AI capabilities on AWS. Additionally, you'll contribute to the broader AWS technical community by sharing your insights and expertise internally, helping to elevate our collective knowledge and approach to AI solutions.
We're looking for candidates with deep technical experience across the AI spectrum, from traditional ML and deep learning to Generative AI and Agentic AI, backed by a strong foundation in mathematics and statistics. This includes hands-on experience with large language models (LLMs) customisation/fine-tuning, inference optimisation, agentic frameworks (e.g. Strands, LangGraph, CrewaI), GenAIOps/AgentOps, Security, RAG systems optimisation & vector stores, prompt/context engineering, etc.
Candidates should have strong communication skills and technical depth, with the ability to engage stakeholders at all levels, from executives to developers. You'll need to translate complex technical concepts into clear, actionable insights and work effectively across diverse teams. Previous experience with AWS is valued but not required, provided you have experience building large-scale solutions. You'll have the opportunity to work directly with senior engineers at customers, partners, and AWS service teams, influencing roadmaps and driving innovation.
Key job responsibilities Build and maintain technical trusted advisor relationships with influential technical decision-makers to drive successful adoption and deployment of AWS services, with particular focus on enterprise-grade AI/ML architectures, Generative AI solutions, and agentic systems.
Architect scalable, secure, and cost-effective solutions leveraging AWS's comprehensive AI stack, from traditional ML services to leading Generative AI offerings. Work closely with customers to understand their business needs and design solutions that optimize both performance and cost while ensuring robust governance and responsible AI practices.
Serve as a thought leader in the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures. Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and GenAIOps best practices. Share insights through AWS Blogs, public speaking events, and technical communities.
Build and nurture an internal AWS community of AI/ML experts, focusing on knowledge-sharing across traditional ML, Generative AI, and Agentic AI domains. Establish best practices for emerging technologies and create enablement materials for the broader AWS technical community.
Collaborate across AWS teams to accelerate customer success with AI/ML implementations. Work with business development, professional services, and support teams to ensure effective adoption of AWS AI services, from proof-of-concept to production deployment.
Act as a technical liaison between customers and AWS engineering teams, ensuring successful implementation of AI solutions while maintaining alignment with AWS's well-architected framework and AI best practices.
A day in the life AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the 8 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 (gender diversity) 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 specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Bachelor's degree in computer science, engineering, mathematics or equivalent
- Experience developing technology solutions and evangelising end-to-end technology roadmaps that guide IT transformations toward cloud computing
- Experience communicating across technical and non-technical audiences and at C-level, including training, workshops, publications
- 7+ years of experience in AI/ML infrastructure, GPU computing, or custom silicon development (e.g., accelerator design,
- compiler/runtime development, HW/SW co-design)
- Deep hands-on experience with GPU optimization, utilization profiling, and workload performance tuning across NVIDIA GPU
- families (H100, B200, B300) or equivalent accelerators
- Experience architecting multi-architecture compute strategies spanning GPU, custom silicon (Trainium/Inferentia), and CPU for
- inference and training workloads
- Experience developing compute roadmaps or capacity planning strategies for large-scale AI infrastructure customers
- Bachelor's degree in computer science, electrical engineering, computer engineering, or equivalent
Preferred Qualifications
- Knowledge of distributed systems design and implementation or equivalent
- Knowledge of large scale automation and workflow management or equivalent
- Knowledge of database design and implementation or equivalent
- Knowledge of presentations and whiteboarding skills with a high degree of comfort speaking with internal and external executives, IT management, and developers
- Experience architecting, migrating, transforming or modernizing customer requirements to the cloud
- Experience with AWS custom silicon (Annapurna/Inferentia/Trainium) or equivalent custom AI accelerator development (runtime drivers, profiling infrastructure, pre/post-silicon validation)
- Experience with ML framework internals (PyTorch, TensorFlow, JAX) and their execution pipelines on custom hardware
- Knowledge of inference optimization techniques: model quantization, batching strategies, token efficiency, pipeline decomposition, and silicon-model matching
- Experience advising customers on GPU-to-Trainium migration paths or multi-accelerator training/inference architectures
- Knowledge of capacity planning, instance right-sizing, and cost optimization for GPU-heavy workloads across regions and availability zones
- Experience partnering with hardware vendor field teams (NVIDIA, AMD) on optimization exercises
- Ability to communicate complex silicon and infrastructure tradeoffs to both deeply technical engineers and C-level executives
- Experience with SageMaker HyperPod, Bedrock Mantle, or equivalent managed AI compute platforms
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, San Francisco - 210,200.00 - 284,300.00 USD annually