Amazon
Job ID: 3090476 | Amazon Web Services, Inc.
Overview We’re seeking a Senior Solutions Architect who combines deep hands-on technical expertise with the ability to build scalable mechanisms that amplify the effectiveness of our Startup Solutions Architecture team. This role requires a rare blend of builder’s depth and strategic impact: someone who can still design, code, and operate systems at scale, while also creating programs, frameworks, and reusable assets that multiply impact across hundreds of startups.
Why This Role At AWS, we’re looking for builders who scale impact. The successful candidate will combine:
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.
Responsibilities
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.
Lead design and ops excellence for Kubernetes/EKS, service mesh, microservices, and serverless-first architectures, with a focus on security, compliance, and observability.
Drive GitOps-first workflows, CI/CD at scale, IaC (Terraform/CDK), and automated testing frameworks; apply SRE best practices for monitoring, incident management, resilience, and scaling.
Advise startups on proprietary data strategy as a moat: data 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.
Publish blogs, whitepapers, open-source repos, and technical presentations that extend reach beyond direct engagements; act as a “co-founder whisperer” translating complex trade-offs into pragmatic startup-stage guidance.
Domain Expertise & Hands-on Impact Principal SAs for Startups should have depth and expertise in one of the following technical domains, with the 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; build and optimize model serving architectures 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), automated testing; apply SRE principles for monitoring, incident management, resilience, and scaling.
Data Strategy & Foundations:
Advise startups on data as a moat: collection, quality, labeling, governance; architect data pipelines and integrate with modern analytics platforms; guide feature stores, vector databases, and lakehouse patterns for ML/RAG; ensure governance across sensitive workloads.
Technical Trend Analysis & Strategic Impact
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. If you do not meet all of the preferred qualifications and skills listed, we encourage candidates to apply. If your career is just starting 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 continue to innovate, trusted by customers from startups to Global 500 companies.
Work/Life Balance We value work-life harmony. Flexible work hours and arrangements are part of our culture. When we feel supported, we can achieve more in the cloud.
Inclusive Team Culture Our culture of learning and curiosity is aided by employee-led affinity groups and events that celebrate diversity.
Mentorship and Career Growth We strive to be Earth’s Best Employer by providing mentorship and resources to help you grow professionally.
Basic Qualifications
10+ years of experience in technology domains (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
Technical expertise in multiple domains including ML/AI systems, cloud-native architectures (Kubernetes, microservices, serverless), DevOps/SRE, and data engineering/strategy; proficiency in Python, Go, TypeScript, and Java.
Track record of scaling impact through enablement programs, mentoring, and establishing best practices that translate individual expertise into organizational capabilities.
Technical leadership credentials including creating technical content, contributing to open-source, delivering thought leadership, and communicating with engineers to C-suite audiences.
Understanding of modern AI/ML ecosystems (LangChain, Hugging Face, vLLM, Ray) with cloud-native security, compliance, and observability.
Preferred Qualifications
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 and brief a C-suite on trends.
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, please visit the accommodations page.
Our compensation reflects cost of labor across several US geographic markets. The base pay ranges from $138,200/year to $239,000/year, with additional compensation as applicable. For more information, please visit the benefits page.
Our position is posted until filled. Applicants should apply via our internal or external career site.
Note:
This job description has been refined for formatting purposes. The original content has been preserved where possible while improving readability and accessibility.
#J-18808-Ljbffr
Overview We’re seeking a Senior Solutions Architect who combines deep hands-on technical expertise with the ability to build scalable mechanisms that amplify the effectiveness of our Startup Solutions Architecture team. This role requires a rare blend of builder’s depth and strategic impact: someone who can still design, code, and operate systems at scale, while also creating programs, frameworks, and reusable assets that multiply impact across hundreds of startups.
Why This Role At AWS, we’re looking for builders who scale impact. The successful candidate will combine:
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.
Responsibilities
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.
Lead design and ops excellence for Kubernetes/EKS, service mesh, microservices, and serverless-first architectures, with a focus on security, compliance, and observability.
Drive GitOps-first workflows, CI/CD at scale, IaC (Terraform/CDK), and automated testing frameworks; apply SRE best practices for monitoring, incident management, resilience, and scaling.
Advise startups on proprietary data strategy as a moat: data 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.
Publish blogs, whitepapers, open-source repos, and technical presentations that extend reach beyond direct engagements; act as a “co-founder whisperer” translating complex trade-offs into pragmatic startup-stage guidance.
Domain Expertise & Hands-on Impact Principal SAs for Startups should have depth and expertise in one of the following technical domains, with the 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; build and optimize model serving architectures 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), automated testing; apply SRE principles for monitoring, incident management, resilience, and scaling.
Data Strategy & Foundations:
Advise startups on data as a moat: collection, quality, labeling, governance; architect data pipelines and integrate with modern analytics platforms; guide feature stores, vector databases, and lakehouse patterns for ML/RAG; ensure governance across sensitive workloads.
Technical Trend Analysis & Strategic Impact
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. If you do not meet all of the preferred qualifications and skills listed, we encourage candidates to apply. If your career is just starting 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 continue to innovate, trusted by customers from startups to Global 500 companies.
Work/Life Balance We value work-life harmony. Flexible work hours and arrangements are part of our culture. When we feel supported, we can achieve more in the cloud.
Inclusive Team Culture Our culture of learning and curiosity is aided by employee-led affinity groups and events that celebrate diversity.
Mentorship and Career Growth We strive to be Earth’s Best Employer by providing mentorship and resources to help you grow professionally.
Basic Qualifications
10+ years of experience in technology domains (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
Technical expertise in multiple domains including ML/AI systems, cloud-native architectures (Kubernetes, microservices, serverless), DevOps/SRE, and data engineering/strategy; proficiency in Python, Go, TypeScript, and Java.
Track record of scaling impact through enablement programs, mentoring, and establishing best practices that translate individual expertise into organizational capabilities.
Technical leadership credentials including creating technical content, contributing to open-source, delivering thought leadership, and communicating with engineers to C-suite audiences.
Understanding of modern AI/ML ecosystems (LangChain, Hugging Face, vLLM, Ray) with cloud-native security, compliance, and observability.
Preferred Qualifications
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 and brief a C-suite on trends.
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, please visit the accommodations page.
Our compensation reflects cost of labor across several US geographic markets. The base pay ranges from $138,200/year to $239,000/year, with additional compensation as applicable. For more information, please visit the benefits page.
Our position is posted until filled. Applicants should apply via our internal or external career site.
Note:
This job description has been refined for formatting purposes. The original content has been preserved where possible while improving readability and accessibility.
#J-18808-Ljbffr