Senior Solutions Architect, Global Energy & Utilities
AI in this role
Architect generative AI solutions and build scalable offerings for energy customers on AWS.
Key job responsibilities
- Work directly with energy customers to architect GenAI solutions, going deep on model selection, fine-tuning strategies, retrieval-augmented generation (RAG) architectures, agentic workflows, and MLOps to deliver production-ready outcomes.
- Develop go-to-market motions with the AWS energy team, creating reusable assets such as reference architectures, proofs of concept, and delivery accelerators that can be deployed across multiple customers.
- Present technical strategies to customer leadership and C-level executives, translating complex GenAI concepts into clear business value and actionable roadmaps.
- Create field enablement materials for the broader solutions architect community, helping them integrate GenAI solutions into customer architectures, and share best practices through blog posts, white papers, and public-speaking engagements at events like AWS Summit and AWS re:Invent.
- Act as a technical liaison between customers and AWS product teams, translating customer feedback into clear requirements that drive product improvements.
A day in the life
You might start your morning reviewing a RAG architecture design for an energy customer's document processing pipeline, refining the retrieval strategy to improve accuracy. By midday, you are co-architecting a GenAI proof of concept with a customer's technical team, walking through model selection trade-offs and building alignment on the deployment approach. Later, you present a solution strategy to customer leadership, then wrap up by packaging the reference architecture from a recent engagement into a reusable accelerator for the broader community.
About the team
Our team works with major energy customers to solve their most complex business challenges using AWS. We collaborate across sales, engineering, professional services, and support to help energy customers build and scale GenAI solutions that create measurable impact. We are investing in generative AI and agentic architectures, and we are looking for builders who want to shape how the energy industry adopts AI.
AWS values a range of experiences. Even if you do not meet all of the qualifications listed in the job description, we encourage candidates to apply. Whether your career is just starting, has followed a non-traditional path, or includes alternative experiences, we want to hear from you. You will find knowledge-sharing, mentorship, and career-advancing resources here, along with an inclusive team culture supported by employee-led affinity groups and learning experiences.
Basic qualifications
- 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 3+ years of design, implementation, or consulting in applications and infrastructures experience
- 10+ years of IT development or implementation/consulting in the software or Internet industries experience
Preferred qualifications
- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communities
- Experience leading or developing high quality, enterprise scale software products using a structured system development lifecycle
- Knowledge of AWS services, market segments, customer base and industry verticals
- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
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, FL, Miami - 153,600.00 - 207,800.00 USD annually
USA, FL, Virtual Location - Florida - 153,600.00 - 207,800.00 USD annually
How we score this
Senior Solutions Architect, Global Energy & Utilities at Amazon scores 70 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.
AI Level 3. The daily work is on or around AI systems, without necessarily building the model: remove AI and the job is hollow.
- AI Level 480 to 100
- AI Level 360 to 79
- AI Level 240 to 59
- AI Level 10 to 39
Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- 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?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- Tell me about a project where generative ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Rag, AI Agents, Fine Tuning, Ml Ops, and Generative AI. 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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