Amazon
Job ID: 3101057 | Amazon Web Services, Inc.
We’re seeking a Principal 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.
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.
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.
Domain Expertise & Hands‑on Impact 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).
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 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.
Why AWS: Amazon Web Services is the world’s most comprehensive and broadly adopted cloud platform. We pioneer cloud computing and continue to innovate, powering customers from startups to global enterprises.
Basic Qualifications
12+ years of specific technology domain experience (software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
Deep 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.
Strong 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.
Preferred Qualifications
Experience building, deploying, and operating systems and infrastructure at hyperscale.
A history of contributions to open‑source or developer communities.
A strong 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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We’re seeking a Principal 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.
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.
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.
Domain Expertise & Hands‑on Impact 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).
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 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.
Why AWS: Amazon Web Services is the world’s most comprehensive and broadly adopted cloud platform. We pioneer cloud computing and continue to innovate, powering customers from startups to global enterprises.
Basic Qualifications
12+ years of specific technology domain experience (software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics).
Deep 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.
Strong 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.
Preferred Qualifications
Experience building, deploying, and operating systems and infrastructure at hyperscale.
A history of contributions to open‑source or developer communities.
A strong 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.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
#J-18808-Ljbffr