Amazon Web Services (AWS) is leading the next phase of AI adoption and seeking a hands-on AI Specialist Solutions Architect (SSA) to help customers transform AI ambition into production-ready solutions.

As part of the AWS sales organization, you'll work with customers facing complex AI/ML challenges that require expert-level knowledge. You'll craft scalable, flexible, and resilient technical architectures while serving as a trusted advisor throughout their generative AI and agentic AI journey.

• Key job responsibilities

• Build trusted technical relationships with customers of all sizes, serving as their advisor for GenAI/ML and Agentic AI adoption across their cloud journey

• Manage technical relationships between AWS and customers, providing recommendations on security, cost, performance, reliability, and operational efficiency to accelerate AI/ML projects

• Act as voice of customer internally, sharing feedback and requirements to influence the AWS GenAI/ML and Agentic features roadmap

• Design cloud-native architectures that link technology to tangible solutions, defining GenAI/ML and Agentic architectural patterns for diverse use cases

• Create and share technical content including whitepapers, code samples, blog posts, and reference architectures; evangelize AWS AI capabilities through workshops, conferences, meetups, and online channels

• Lead technical deep dives and workshops, contributing reusable code, reference architectures, and technical assets for the broader engineering organization

A day in the life
Your day will be a dynamic blend of technical problem-solving and strategic collaboration. You'll engage with customers across diverse industries, diving deep into their unique AI challenges and crafting innovative cloud-native solutions. From architecting complex AI systems to developing reference implementations, you'll be at the forefront of technological innovation.

About the team
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 in the cloud.

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 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

• 4+ years of experience in designing and implementing application and infrastructure solutions
• 3+ years of technical customer engagement and resource management experience
• 3+ years of production AI system design experience
• Hands-on experience with cloud platforms and AI/ML services to build secure AI environments and implement RAG using embeddings, vector stores, and semantic search.
• Strong communication skills with ability to influence technical and business decision-makers across diverse audiences

Preferred Qualifications

• Cloud technology certification (AWS, Azure, or GCP Solutions Architect or equivalent)
• Advanced degree in computer science, mathematics, statistics, machine learning, or related quantitative field
• Experience with LLM optimization techniques (e.g., LoRA/QLoRA, Instruction Tuning, RLHF) for domain-specific tasks
• Expertise in architecting AI systems for highly regulated or security-sensitive environments (Financial Services, Healthcare, Public Sector)
• Proven track record of leading complex, innovative technology initiatives with measurable business impact
• Hands-on experience with cloud AI/ML services (e.g., AWS Bedrock/Sage Maker, Azure OpenAI Service/Azure ML, Google Vertex AI) for production RAG implementations

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.