Sr. GenAI Specialist PSA , Solutions Architecture

Amazon is hiring a Sr. GenAI Specialist PSA , Solutions Architecture. It pays $154k-$208k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Works on AI ●●●○ is how Level rates this solutions architect role: the daily work is on AI products, without building the model.
The posting mentions LangChain, Bedrock and Pinecone among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

LangChainBedrockPineconepgvectorSageMaker

prompt-engineeringragllm-integrationai-agentsfine-tuningml-opsai-evaluationai-safety

Application deadline: Nov 8, 2026

Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on Sr. Partner Solutions Architect (PSA) focused on Generative AI. In this role, you will work directly with AWS Partners — ISVs, SIs, and consulting firms — to help them build, differentiate, and scale GenAI solutions on AWS that drive measurable customer outcomes and accelerate partner-led revenue growth.

AWS Partner Solutions Architects are technologists with deep domain-specific expertise who operate at the intersection of partner strategy and technical depth. As part of the AWS partner organization, you will engage with partners who are building GenAI practices and products — guiding them on scalable, production-ready architectures while enabling them to independently deliver GenAI solutions to their end customers.

This role focuses on converting partner GenAI ambition into repeatable, scalable offerings that can be built once and delivered to many customers. You must be comfortable going deep on model selection, fine-tuning strategies, RAG architectures, agentic workflows, and MLOps — and equally comfortable enabling partner technical teams, co-architecting joint solutions, and presenting technical strategies to partner leadership and C-level executives.

You will help partners achieve AWS competencies and service validations, develop joint go-to-market motions, and create reusable assets (reference architectures, Proofs of Concept, and delivery accelerators) that multiply partner impact across their customer base. You think in terms of leverage — enabling one partner to serve hundreds of customers — rather than solving one customer problem at a time.

We are looking for someone who doesn't just talk about GenAI, but has built and shipped GenAI solutions in real-world settings — and can transfer that expertise to partners so they can do the same at scale.

Key job responsibilities
Technical Advisory & Partner Enablement: Build deep technical relationships with AWS Partners (ISVs, SIs, consulting firms) as their trusted GenAI/ML advisor — guiding them in designing cloud-native architectures for LLM-powered applications, agentic systems, and multi-modal AI solutions they can repeatedly deliver to customers.

Hands-on Enablement: Co-build with partner engineering teams through end-to-end GenAI development — model selection, RAG implementation, fine-tuning, prompt engineering, and inference optimization — accelerating their time-to-market.

Scalable Offerings: Create reusable reference architectures and delivery accelerators that partners can package into repeatable GenAI offerings across conversational AI, document processing, knowledge assistants, and autonomous agents.

Agentic AI: Enable partners to productize LLM-powered agents using Amazon Bedrock Agents, AgentCore, and custom frameworks.

Partner Engagement: Engage partner leadership and technical teams, drive AWS Competency attainment, and develop lighthouse partners.

Voice of Partner: Advocate for partner ecosystem needs to influence AWS GenAI product roadmap.

Practice Development: Guide partners in scaling GenAI practices — skilling, methodology, and GTM enablement.

Cross-functional Collaboration: Work closely with Partner Development Managers, Partner Sales Managers, AWS service teams, and the broader SA community to accelerate partner-led GenAI adoption at scale.

About the team
About AWS
Diverse Experiences
AWS 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.

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

- 7+ years of design/implementation/operations/consulting with distributed applications experience
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership
- 5+ years customer-facing experience building production AI/ML systems
- Hands-on GenAI implementation: LLM integration, RAG (vector databases, semantic search), agentic workflows, prompt engineering, model evaluation, and inference optimization
- Experience with AWS AI/ML services (Amazon Bedrock, SageMaker, AgentCore) or equivalent cloud AI platforms

Preferred qualifications

- Production GenAI track record — Demonstrated experience shipping GenAI/LLM applications to production at scale, not just POC/prototype stage.
- Agentic AI depth — building multi-step, tool-using agents with orchestration frameworks (Bedrock Agents, Strands Agents SDK, LangChain, or custom)
- MLOps/LLMOps — CI/CD pipelines, model versioning, monitoring, and automated evaluation
- Vector database expertise (OpenSearch Serverless, pgvector, Pinecone)
- Multi-modal AI — Experience working with vision-language models, image generation, or audio/video understanding models.
- Security & governance — guardrails, responsible AI, compliance in enterprise settings
- AWS Certifications (ML Specialty, SA Professional) preferred
- 10+ years in software engineering, AI/ML, or cloud architecture

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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, CO, Denver - 153,600.00 - 207,800.00 USD annually
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually

How we rate this

Sr. GenAI Specialist PSA , Solutions Architecture at Amazon rates 71 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Sr. GenAI Specialist PSA , Solutions Architecture is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The listed salary is $154k-$208k a year.
The role is based in US, VA, Herndon.
The job was posted on July 9, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Prompt engineeringRAGLLM IntegrationAI agentsFine-tuningML OpsAI EvaluationAI Safety

Also common in solutions architect jobs at this level

Python Azure Google Cloud Machine learning SQL Kubernetes

Pay

This job starts at: $154k
Typical solutions architect job: $169k

This posting starts 9% below the typical solutions architect job. See solutions architect jobs

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
How would you design a retrieval step so the model answers from real data instead of guessing?
How have you integrated a large language model into a production application?
How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?

Adapt your resume

List these exact terms on your resume: Prompt engineering, RAG, LLM Integration, AI agents, and Fine-tuning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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