> Markdown version of [/jobs/ext/3547873-startup-solutions-architect-early-stage-startups](https://www.wearedevelopers.com/jobs/ext/3547873-startup-solutions-architect-early-stage-startups). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Startup Solutions Architect, Early Stage Startups - **Company:** Amazon.com, Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $151,000.0 - $204,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Systems Engineering, Automated Storage and Retrieval Systems, Cloud Computing, Data Infrastructure, Machine Learning, Software Engineering, Retrieval-Augmented Generation, Claude Code, Generative AI, Agentic-AI, AI Platforms, Kubernetes, Data Analytics, Elastic Beanstalk, Data Pipelines - **Published:** October 1, 2026 - **Apply:** https://dejobs.org/x/x/995B5903E9C04FB4B27221345559D7FE/job/ ## About the Role * 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, * 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 ## Description * 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