Applied AI Specialist Solutions Architect (SA)

Are you passionate about generative AI, agentic AI, and the large language models and autonomous systems reshaping how businesses operate? Are you excited by the idea of helping some of the world's largest technology companies put that potential into production? We'd love to hear from you.

Generative AI and agentic AI are changing how people work. Generative AI is producing code, content, and analysis on demand, while agentic systems are taking on multi-step business tasks with growing autonomy, from customer support and software delivery to financial operations and supply chain logistics. Training and running the foundation models and agents behind this shift takes serious compute, which is why the cloud, and AWS in particular, is where this work happens. We're looking for someone who wants to help enterprise customers turn that potential into real, production systems.

In this role, you'll be the go-to technical expert for designing scalable, secure, and cost-effective generative AI and agentic AI solutions using services like Amazon Bedrock, Amazon Bedrock AgentCore, and the Strands Agents SDK. You'll balance what's newest in AI with what large enterprises actually need to run in production: reliability, governance, and compliance. That means helping organizations build responsible AI practices, from choosing and customizing foundation models to running multi-agent systems in production, backed by clear governance frameworks and secure AI pipelines.

You'll work directly with some of AWS's largest and most strategic technology customers as they build out their AI roadmap, helping their teams stand up practical GenAIOps and AgentOps practices and enterprise-grade AI architectures that deliver measurable business value. Day to day, that means sitting down with customer engineering teams to understand what they're trying to build, then turning that into concrete technical architectures spanning model selection, orchestration, and agent deployment. You'll present AWS services and solutions, write up the patterns that work so others can reuse them, and help customers, partners, and independent software vendors (ISVs) get the most out of generative AI and agentic AI on AWS. You'll also help raise the bar across AWS's technical community by sharing what you learn along the way.

We're looking for people with deep, hands-on experience across the applied AI spectrum: generative AI and agentic AI, plus a working knowledge of the model training and fine-tuning that sits underneath them. That includes real experience with large language model (LLM) customization and fine-tuning, inference optimization, agentic frameworks (for example Strands Agents SDK, LangGraph, CrewAI), GenAIOps and AgentOps, AI security, retrieval-augmented generation (RAG) and vector store optimization (for example vector engines and stores such as Amazon S3 Vectors), and prompt and context engineering. Experience with AWS applied AI services such as Amazon Bedrock, Amazon Bedrock AgentCore, Amazon Q Developer, Amazon Quick, and Kiro is a plus, but not required.

You should be a strong communicator who can talk comfortably with anyone from a developer to a CEO, translating complex technical ideas into guidance people can actually act on. Previous AWS experience is nice to have but not required, as long as you've built and run large-scale AI systems in production. You'll get to work directly with senior engineers at customers, partners, and AWS service teams, shaping roadmaps and pushing applied AI forward.

Key job responsibilities

Build and maintain technical trusted-advisor relationships with influential technical decision-makers to drive adoption and deployment of AWS services, with particular focus on enterprise-grade generative AI solutions, agentic systems, and the foundation models and infrastructure that support them.

Architect scalable, secure, and cost-effective solutions using AWS's applied AI stack, including Amazon Bedrock, Amazon Bedrock AgentCore, Amazon SageMaker AI, and purpose-built AI infrastructure such as AWS Trainium and Inferentia. Work closely with customers to understand their business needs and design solutions that balance performance and cost while maintaining clear governance and responsible AI practices.

Serve as a thought leader in the applied AI space by developing technical content and practical implementations that showcase modern AI architectures. Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, multi-agent systems built with Amazon Bedrock AgentCore and the Strands Agents SDK, and GenAIOps and AgentOps best practices. Share insights through AWS Blogs, public speaking engagements, and technical communities.

Build and grow an internal AWS community of applied AI experts, focused on knowledge-sharing across generative AI and agentic AI domains. Establish best practices for emerging agent frameworks and tooling, and create enablement materials for the broader AWS technical community.

Work across AWS teams to accelerate customer success with applied AI implementations. Partner with business development, professional services, and support teams to drive 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 the AWS 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 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.

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

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

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