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Summary
20+ years of experience in software architecture and technical leadership.
Expertise in enterprise architecture, distributed systems, microservices, cloud infrastructure, and AI automation.
Led R&D initiatives and integrated emerging technologies into production.
Established architecture standards, governance frameworks, and CI/CD practices.
Developed reusable libraries and tools to improve scalability and code quality.
Experienced in infrastructure-as-code and highly available cloud-native architectures.

Role Overview
We are looking for a Technical Solution Architect to drive architectural strategy and technical direction across enterprise engineering initiatives.
The role involves contributing to the design and implementation of AI-driven automation solutions aimed at transforming manual decision-making workflows into reliable, scalable, and auditable systems.
Working within a cross-functional engineering environment, the architect collaborates with AI Platform, IT, DevOps, and other technical stakeholders to ensure successful integration of AI capabilities into production environments.

Key Responsibilities
Architecture Strategy: Define and drive technical architecture strategies aligned with business objectives, ensuring scalability, reliability, and long-term maintainability.
Architecture Governance: Establish and promote enterprise architecture standards, engineering principles, and governance frameworks across multiple engineering teams.
AI and Automation Architecture: Lead architectural initiatives focused on replacing manual decision-making processes with AI-assisted systems, ensuring reliability, auditability, and production readiness.
Technical Leadership: Collaborate with AI Platform, IT, DevOps, and engineering teams to integrate new solutions into existing enterprise environments.
Technology Evaluation: Research and evaluate emerging technologies, tools, and frameworks, identifying opportunities for their adoption and integration.
Engineering Excellence: Drive continuous improvement initiatives focused on engineering efficiency, code quality, system scalability, and technical consistency.
Shared Components and Services: Oversee the development and adoption of reusable internal libraries, common components, and shared services across engineering teams.
Cloud and Delivery Architecture: Define and standardize deployment patterns, CI/CD practices, and cloud-native operational architectures.
Infrastructure and Automation: Promote infrastructure-as-code, pipeline automation, and highly available operational architectures.

Technical Environment
Architecture: Enterprise Architecture, Microservices, Cloud-Native Architecture
AI and Automation: AI-Assisted Systems, Intelligent Automation, Decision-Making Workflows
Infrastructure: Infrastructure-as-Code, High-Availability Architectures
CI/CD: Continuous Integration and Continuous Deployment, Pipeline Automation
Engineering Practices: Architecture Governance, Engineering Standards, Reusable Libraries and Shared Services

Collaboration
Cross-functional engineering teams
AI Platform teams
IT and DevOps
Technical and business stakeholders

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