Principal Solutions Architect

Position Overview
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.

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.


Key job responsibilities
Key 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

* 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.