Senior Solutions Architect, Amazon

• 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
• * 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)
• 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

Desirable

• This role offers the chance to shape how AWS engages startups at scale — while working at the frontier of cloud + data + AI innovation
• * 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
• * 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
• * Lead design and ops excellence for Kubernetes/EKS, service mesh, microservices, and serverless-first architectures
• * Ensure security, compliance, and observability in containerized workloads
• * 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
• * 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
• * 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
• * 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