Amazon Senior Solutions Architect 

United States, California, San Francisco 

988945939

Why This Role* Deep technical expertise (still hands-on)
* Scalable mechanism design (programs, frameworks, enablement)
* Startup empathy (credible in front of developers and co-founders)
* AI/data native perspective (helping startups turn data into their moat)This role offers the chance to shape how AWS engages startups at scale — while working at the frontier of cloud + data + AI innovation.
Key job responsibilities
Technical Leadership & Mechanism Building* Design and implement scalable programs, reusable assets, and automation tools that amplify the impact of the Startup SA org.
* Create reference architectures, IaC templates, and enablement content to accelerate solution delivery across startups.
* Develop systematic approaches to capture, codify, and share technical insights from the field back into the org.
* Mentor SAs and drive technical upskilling programs that elevate the entire team’s capabilities.Principal SAs for Startups should have depth and expertise in one of the following technical domains, but the technical curiosity to become proficient in all:* ML/AI Infrastructure:
* Architect training and inference systems at scale (distributed training, LoRA/QLoRA, quantization, GPU/TPU optimization).
* Design end-to-end ML pipelines and MLOps workflows (data prep, labeling, model registry, deployment).
* Build and optimize model serving architectures and inference systems for cost and latency.
* Cloud Native & Kubernetes:
* Lead design and ops excellence for Kubernetes/EKS, service mesh, microservices, and serverless-first architectures.
* Ensure security, compliance, and observability in containerized workloads.
* DevOps & Reliability:
* Drive GitOps-first workflows, CI/CD at scale, IaC (Terraform/CDK), and automated testing frameworks.
* Apply SRE best practices: monitoring, incident management, resilience, and scaling patterns.
* Data Strategy & Foundations:
* Advise startups on proprietary data strategy as a moat: collection, quality, labeling, governance.
* Architect data pipelines (ETL/ELT, streaming, orchestration) and integrate with modern analytics platforms (Snowflake, Redshift, BigQuery, Databricks).
* Guide adoption of feature stores, vector databases, and lakehouse patterns to enable ML/RAG use cases.
* Ensure compliance and governance across sensitive workloads (GDPR, HIPAA, SOC2).* Maintain deep understanding of emerging technical trends in GenAI, cloud, and data ecosystems.
* Translate insights into actionable guidance for startups and scalable mechanisms for the org.
* Provide forward-looking perspectives on technology adoption, evolution, and competitive advantage.Scaling & Developer Enablement* Build repeatable solutions and reference architectures addressing common startup pain points.
* Publish blogs, whitepapers, open-source repos, and technical presentations that extend reach beyond direct engagements.
* Act as a “co-founder whisperer” — translating complex technical trade-offs into pragmatic startup-stage guidance.About the team
Diverse Experiences
Amazon 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 AWSWork/Life BalanceInclusive Team CultureMentorship and 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.

- 10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Technical expertise in multiple domains including ML/AI systems, cloud-native architectures (Kubernetes, microservices, serverless), DevOps/SRE practices, and data engineering/strategy, with advanced proficiency in languages like Python, Go, TypeScript, and Java.
- Demonstrated track record of scaling technical impact through building enablement programs, mentoring teams, and establishing best practices that transform individual expertise into organizational capabilities.
- Technical leadership credentials including creating technical content, contributing to open-source projects, delivering thought leadership, and effectively communicating with audiences from engineers to C-suite executives.
- Comprehensive understanding of modern AI/ML ecosystems (LangChain, Hugging Face, vLLM, Ray) combined with expertise in cloud-native security, compliance, and observability frameworks to build production-grade systems.

- Experience building, deploying, and operating systems and infrastructure at hyperscale.
- Contributions to open-source or developer communities.
- A portfolio of technical publications, talks, or thought leadership.
- The credibility to pair-program with a founder one day, then brief a C-suite on trends the next.Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.