Solution Enterprise Architect AWS
WinWire Technologies
Experience: 20+ Years Location: We are seeking a highly experienced Enterprise Solution Architect to design and govern large‑scale, multi‑cloud solutions across Data, Applications, Infrastructure, and AI‑first engineering landscapes.
Define and govern enterprise‑wide architecture across Data, Applications, Cloud, and AI‑enabled platforms.
Own solution design for complex, distributed, and multi‑cloud systems (Azure primary; AWS/GCP secondary).
Lead architecture reviews, trade‑off analysis, and technology selection aligned with Well‑Architected and TOGAF principles.
Embed SRE, DevOps, and reliability engineering practices (SLOs, error budgets, observability).
Drive AI‑first engineering adoption , including AI‑assisted development, testing, monitoring, and DevOps automation.
Support solutioning, pre‑sales, RFPs, and executive‑level presentations when required.
20+ years of comprehensive IT experience, including 8+ years in a Solution Architect or Enterprise Architect role in either Data Engineering & Analytics or Application Development & Infrastructure as the primary domain.
- 4+ years of cross-domain experience in the complementary domain (Data or App Dev/Infra), demonstrating architectural breadth.
- Hands-on, deep expertise in Microsoft Azure, architecture, design, and implementation across compute, storage, networking, data, and security services; Working proficiency in AWS and/or GCP, capable of designing, reviewing, and governing multi-cloud workloads across cloud platforms.
- Practical application of Well-Architected Frameworks (Azure, AWS, or GCP) in production solution design, demonstrated hands-on implementation, not theoretical familiarity.
- Strong understanding of SRE principles, SLOs, error budgets, reliability patterns, and observability frameworks, with experience embedding these into engineering programs.
- Demonstrated ability to leverage AI tools (GitHub Copilot, AI-assisted code review, automated testing, intelligent monitoring and incident analysis) to automate and standardize engineering practices, achieving simultaneous, measurable gains in team productivity and solution quality.
- Robust integration skills across custom applications, data platforms, and COTS solutions.
- Hands-on experience with CI/CD, DevOps toolchains, infrastructure-as-code, and automation practices.
- Influence architecture and reliability practices at enterprise scale across multi-cloud environments.
Work across diverse engineering domains including cloud, software, data, AI, and platforms.
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