Please find the JD below:

Location - Bangalore (work from client location)

We are seeking an experienced Enterprise AI Architect to lead the organization's AI transformation initiatives and establish enterprise-wide AI architecture, governance, and implementation frameworks. The ideal candidate will bridge business strategy, enterprise architecture, data platforms, cloud infrastructure, and AI technologies to drive scalable and responsible AI adoption across the enterprise.The Enterprise Architect will define AI roadmaps, oversee AI platform architecture, guide solution delivery teams, and ensure alignment between AI investments and business objectives.

Key Responsibilities

Enterprise AI Strategy & Architecture

- Define and maintain enterprise-wide AI architecture strategy aligned with business goals.
- Develop current-state, target-state, and transition-state architecture for AI adoption.
- Establish AI reference architectures, standards, and best practices.
- Create multi-year AI transformation roadmaps.

AI Platform Architecture

- Design scalable AI/ML platforms supporting Generative AI, Machine Learning, Predictive Analytics, and Intelligent Automation.
- Define architecture for AI model lifecycle management (MLOps/LLMOps).
- Establish reusable AI services, APIs, and enterprise AI capabilities.
- Evaluate and recommend AI technology platforms and frameworks.

Data & AI Integration

- Partner with Data Architects to define enterprise data architecture supporting AI initiatives.
- Design integration patterns between AI platforms, business applications, data lakes, and enterprise systems.
- Ensure data quality, governance, lineage, and security requirements are met.

Cloud & Infrastructure Architecture

- Define cloud architecture strategies for AI workloads on AWS, Azure, or GCP.




- Architect GPU-enabled infrastructure and scalable AI environments.
- Lead adoption of cloud-native AI services and platforms.
- Ensure high availability, scalability, and performance of AI solutions.

Governance, Security & Responsible AI

- Establish AI governance frameworks and architecture review processes.
- Ensure compliance with security, privacy, regulatory, and ethical AI standards.
- Define controls for model explainability, fairness, transparency, and risk management.
- Partner with cybersecurity and compliance teams to mitigate AI-related risks.

Stakeholder Management

- Collaborate with CIO, CTO, Chief Data Officer, business leaders, and technology teams.
- Translate business opportunities into AI-enabled solutions.
- Present architecture strategies, roadmaps, and recommendations to executive leadership.
- Lead architecture governance boards and decision-making forums.
- Winning new deals, creating opportunities, generating revenues, investments, and product consulting.

Emerging Technology Evaluation

- Evaluate Generative AI, Agentic AI, Large Language Models (LLMs), AI Agents, RAG, Knowledge Graphs, and Intelligent Automation platforms.
- Conduct architecture assessments and proof-of-concepts.
- Recommend innovative solutions to improve business outcomes.

Qualifications

- Bachelor's degree in Computer Science, Engineering, or related field.
- Master's degree preferred.
- 15+ years of IT experience with 5+ years in Enterprise Architecture.
- Experience leading enterprise-wide transformation programs.
- Proven experience implementing AI/ML and Generative AI solutions at scale.

Preferred Certifications

- TOGAF/Archimate/Zachman
- AWS Certified Solutions Architect Professional
- Microsoft Certified: Azure Solutions Architect Expert
- Google Skilled Cloud Architect
- AI/ML Certifications from major cloud providers

📌 Enterprise Architect - AI Implementation - Bangalore (client location) (Bengaluru)
🏢 Dappverse Computing Chennai
📍 Bengaluru