Responsibilities

1. Enterprise AI Strategy & Architecture

Define and maintain the enterprise AI architecture roadmap.
Develop reference architectures for GenAI, Agentic AI, Machine Learning, and Intelligent Automation Solutions.
Evaluate AI platforms, frameworks, LLM providers, and emerging technologies.
Establish reusable architecture patterns and standards for enterprise-wide AI adoption.
Align AI investments with organizational technology and business strategies.

2. Solution Architecture & Design

Define end-to-end system architecture and technical roadmaps.
Create High-Level Design (HLD) and detailed architecture artifacts.
Ensure scalability, performance, security, reliability, and maintainability.
Evaluate technology options and recommend architectural patterns.
Review architectural designs for strategic initiatives and AI programs.

3. AI Platform & Innovation Leadership

Design enterprise AI platforms and shared services.
Drive adoption of AI development frameworks, LLM gateways, agent frameworks, and orchestration platforms.
Establish standards for prompt engineering, model lifecycle management, vector databases, and knowledge retrieval solutions.
Lead proof-of-concepts, pilot initiatives, and innovation programs.
Assess build-vs-buy decisions for AI and automation solutions.

4. Business & Stakeholder Alignment

Collaborate with business leaders, product owners, business analysts, and executive stakeholders to identify AI opportunities.
Translate business objectives into scalable AI solutions.
Develop business cases and architecture recommendations for leadership review.
Present architecture strategies and transformation roadmaps to governance boards and executive leadership.

5. Technical Leadership

Lead architecture reviews, design workshops, and technical strategy discussions.
Mentor architects, engineers, and development teams on AI technologies and enterprise architecture practices.
Define engineering standards, design principles, and best practices.
Foster an innovation culture through education, workshops, and technical leadership.

6. Integration & Enterprise System Design

Design integrations across enterprise applications, cloud platforms, APIs, ERP, CRM, and data platforms.
Define data flows, enterprise integration patterns, interface contracts, and dependencies.
Ensure interoperability between AI platforms and existing enterprise systems.
Support modernization and digital transformation initiatives across multiple business functions.

Qualifications

Preferred Qualifications

12+ years of experience in software engineering, solution architecture, or enterprise architecture.
5+ years of experience leading cloud-native and enterprise-scale platforms.
Strong experience with AI/ML, Generative AI, Agentic AI, Intelligent Automation, and enterprise integration.
Hands-on knowledge of Azure OpenAI, AWS AI Services, Anthropic, Google Vertex AI, or equivalent platforms.
Deep understanding of enterprise architecture, cloud platforms, APIs, integration frameworks, DevOps, and security practices.
Experience with architecture governance frameworks and Architecture Review Boards.
Strong leadership, communication, stakeholder management, and strategic planning skills.

Expected Outcomes

Accelerate AI adoption across enterprise applications and business operations.
Establish reusable AI architecture patterns and governance frameworks.
Improve software engineering productivity through AI-assisted development.
Reduce delivery timelines and improve business agility.
Strengthen enterprise architecture standards and technical governance.
Build a sustainable AI capability supporting long-term organizational growth.

Keys to Success

• Building collaborative relationships
• Decision making
• Drive results
• Foster innovation
• Personal energy
• Self-leadership

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Sys Design Architect V

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