Startup Solutions Architect, Early Stage Startups
You\'ll work across AI/ML, FinTech, ClimateTech, healthcare, consumer, B2B SaaS, and whatever gets invented next, with many of these companies coming straight out of Y Combinator and other top accelerators or freshly backed by leading VC firms. They need a trusted technical voice in their corner from day one, and you get to be it. Picture a small team with a technical founder and maybe a couple of engineers, moving fast with Claude Code, Codex, and whatever tool shipped last week, trying to make every product, architecture, and business decision at once. There\'s no VP of Engineering to align with, no platform team to hand things off to, and no multi-quarter roadmap, so for the startups you work with you become the closest thing they have to a fractional CTO or chief architect. That\'s what makes this an adventure rather than a support role: you and the founders are figuring it out together, and a single good decision can save six months of runway while a bad one can quietly sink the whole thing.
The work is bigger than architecture, and it changes week to week. One week you\'re helping a team understand the architecture their coding agent quietly built for them and untangling the decisions they didn\'t realize they\'d made, the next you\'re figuring out how to scale after an unexpected viral launch, and the week after that you\'re working a compliance problem with a FinTech startup that has to move fast but can\'t cut corners, or talking a founder through a hard pivot and helping them separate what they\'ve already built from where the data says they should actually go. You\'ll prototype alongside them, experiment with frontier AI, and carry what you learn from hundreds of founders back into AWS so the products we build reflect what the leading edge actually needs.
We hire for a specific kind of person, and it starts with founder empathy over enterprise process. You get that every dollar spent on infra is a dollar not spent on talent or growth, that their timeline is measured in months of runway, and that they\'re emotionally all-in on this idea, so you earn trust by genuinely caring whether the team survives rather than by showing off enterprise-grade architecture. That empathy shows up as survival-first thinking: before you recommend anything, you understand their runway, their burn, their signals of product-market fit, and their next milestone, whether that\'s demo day, a fundraise, or a first paying customer.
To advise this well you have to see the full stack of the business, letting technical choices, product, business model, runway, and the founder\'s own risk tolerance all inform your recommendations, because you can\'t advise on architecture without understanding burn rate. You stay a builder at heart, since you don\'t stop being an engineer when you join this team; you prototype, write code, and get your hands dirty with new models, Bedrock, agents, and RAG because that\'s how you stay credible with people who build for a living. And you act as a scout for the future, spotting when a single startup\'s tool choice becomes a cohort-wide trend twelve to twenty-four months before the rest of the market, then carrying that signal back to AWS product and service teams. You don\'t have to already be a Solutions Architect to do this. Great people on this team have come from founding-engineer roles, senior software engineering, AI engineering, and traditional SA backgrounds, and if you\'re an excellent builder who loves customers, we can teach you the AWS you need.
Key job responsibilities
- Act as a trusted technical advisor to a portfolio of early-stage founders, designing architectures that are right-sized for where they are today and built to grow if and when they scale
- Get hands-on: prototype, build reference patterns, and demo working solutions alongside founders rather than handing them a generic playbook
- Help founders understand and improve the architectures their coding agents generated, making sense of the decisions and tradeoffs baked into what they\'ve already shipped
- Help startups navigate the fast-moving GenAI landscape, from selecting the right foundation models and AI services to shipping production-ready AI-powered products
- Guide founders through the real challenges of building GenAI applications, including model cost, latency, accuracy, safety, and AI best practices
- Help founders make pragmatic build-and-scale decisions, including when to keep architectures disposable and adaptable while the direction is still being validated
- Stay technically sharp by experimenting with new models, agent frameworks, and emerging tools, so you can advise credibly across the entire stack
- Build and deepen relationships across San Francisco\'s startup ecosystem, including top accelerators like Y Combinator, incubators, and leading VC firms
- Be a voice for your founders, connecting their feedback and needs directly to AWS product and engineering teams to shape the tools being built for them
- Scout emerging technology trends across the startups you work with and translate those signals back into AWS product roadmaps
- Share your expertise at startup events, demo days, and developer meetups across the San Francisco ecosystem to build trust and visibility in the community
BASIC QUALIFICATIONS
- 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 2+ years of design, implementation, or consulting in applications and infrastructures experience
- Experience with designing and building application using AWS services such as Lambda, AWS Elastic Beanstalk, Kubernetes
- Experience conveying complex technical concepts to both technical and business audiences
- Hands-on experience building with GenAI, such as foundation models, agents, RAG, or fine-tuning, in a prototype or production setting
PREFERRED QUALIFICATIONS
- Experience as a startup founder, founding engineer, or early engineer at a pre-Series A company
- Fluency with modern agentic coding tools (e.g. Claude Code, Codex) and the ability to reason about the architectures they generate
- Experience shipping GenAI applications to production, including managing model cost, latency, accuracy, and safety
- Depth in at least one technical or industry domain (e.g. AI/ML, data & analytics, security, FinTech, healthcare) paired with broad full-stack fluency
- Experience building data foundations for AI products, such as vector databases, data pipelines, or retrieval systems
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 - 151,000.00 - 204,300.00 USD annually
