puestos en Amazon en United States

Are you passionate about Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), Generative AI and Agentic AI? Are you excited by the challenge of driving production usage of ML and AI at scale? Come join us!

ML and AI, especially Generative AI and Agentic AI, are rapidly growing in importance. We're witnessing the revolutionary 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 transforming every industry. Given the massive computational scale required for developing AI models, particularly large language models and autonomous agents, the cloud is an ideal place to deploy AI models, and Amazon Web Services (AWS) is the leader in the deployment of AI. We're looking for someone passionate and deeply excited about this space. Someone who is devoted to helping customers understand how AI can make a big difference to their businesses.

As an AI/ML Specialist Solutions Architect (SA), you will be the Subject Matter Expert (SME) 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 crucial in helping organizations build responsible AI practices, from traditional ML to advanced Generative AI and Agentic AI systems, while implementing robust governance frameworks and secure AI pipelines that scale efficiently.

Part of the Data and AI Specialist Solutions Architecture team, you will guide customers through their AI transformation journey, working closely with other Specialist SAs in Big Data, Databases and Analytics, Storage, Containers, Accelerated Compute and Business Development teams. You'll help customers establish scalable MLOps practices and create sustainable, enterprise-grade AI architectures that deliver measurable business value. Your role includes developing technical content, reference implementations, and presentations to enable customers, partners, and ISVs to fully leverage AI/ML and Generative AI on AWS. Additionally, you will create field enablement materials to help the broader SA population understand and integrate AWS AI/ML and Generative AI solutions into customer architectures.

You must have deep technical experience across the AI spectrum - from traditional ML and deep learning to Generative AI and Agentic AI - backed by a strong mathematics and statistics foundation. This includes hands‑on experience with large language models (LLMs), foundation models, and autonomous agent frameworks, alongside expertise in implementing RAG systems, designing prompt engineering frameworks, and developing multi‑agent systems. You should be proficient with both commercial and open‑source technologies, including popular frameworks like LangChain, Hugging Face, and PyTorch, as well as vector databases and embedding models. Your comprehensive understanding of the AI/ML ecosystem, including leading vendors, emerging startups, and key open‑source projects, will be crucial in helping AWS customers create robust ML pipelines, establish effective MLOps practices, and build future‑proof AI architectures.

Candidates must have great communication skills and be very technical, with the ability to engage AWS customers at any level, from executives to developers. Previous experience with AWS is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and AWS service teams, influencing their roadmaps and driving innovation.

If you are someone who enjoys innovating, likes solving hard problems and working on the latest and greatest technology, we would love to have you on the team.

AWS Global Services includes experts from across AWS who help our customers design, build, operate, and secure their cloud environments. Customers innovate with AWS Professional Services, upskill with AWS Training and Certification, optimize with AWS Support and Managed Services, and meet objectives with AWS Security Assurance Services. Our expertise and emerging technologies include AWS Partners, AWS Sovereign Cloud, AWS International Product, and the Generative AI Innovation Center. You’ll join a diverse team of technical experts in dozens of countries who help customers achieve more with the AWS cloud.

• 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 autonomous agent 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 MLOps 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.
• Drive technical excellence as a key member of the Data and AI Specialist team. 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.

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.

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.

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.

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.

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.

• Bachelor’s degree in computer science, engineering, mathematics or equivalent
• 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
• Experience communicating across technical and non‑technical audiences, including executive level stakeholders or clients
• 10+ years of combined experience in AI/ML and related technologies, with deep expertise in traditional machine learning and deep learning. Must have experience building production‑grade AI systems, complemented by practical knowledge of modern Generative AI technologies (LLMs, foundation models, RAG systems) and autonomous agent frameworks. Strong background in AI architecture patterns and MLOps practices, with demonstrated ability to design and deploy enterprise‑grade AI solutions at scale.

• Experience in a technical role within a sales organization
• Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field, with research or practical experience in emerging AI technologies. Published work or significant contributions to AI/ML open‑source projects, particularly in Generative AI or autonomous systems, would be highly valued.