Enterprise Architect

Job Summary:

We are seeking an experienced Enterprise Architect to design and govern the enterprise-wide AI platform architecture by bringing Architecture best principles.

This role will be responsible for defining the technical vision, architectural standards, and integration patterns for AI/ML, Generative AI and Agentic AI capabilities across the organization. The ideal candidate will bridge business strategy with technical implementation, ensuring scalable, secure, and interoperable AI platform solutions that align with enterprise objectives and drive digital transformation.

The candidate will work closely with clients to understand their needs and guide them through their AI transformation journey, from strategy to implementation. This role demands a deep understanding of industrial systems, intelligent automation, data ecosystems, and AI-driven innovation to build resilient, future-ready digital architectures.

Key Responsibilities:

AI Platform Architecture Design: Define and maintain the enterprise AI & Generative AI platform architecture, including reference architectures, design patterns, and technical standards for AI/ML workloads, data pipelines, and model lifecycle management. Technology Strategy & Roadmap: Develop comprehensive technology roadmaps for AI platform evolution, evaluating emerging technologies and their alignment with business strategy and enterprise architecture principles.

Integration Architecture: Design integration patterns and APIs for seamless connectivity between AI platforms and existing enterprise systems, ensuring data consistency, security, and performance optimization. Governance & Standards: Establish architectural governance frameworks, design principles, and best practices for AI platform development, including data governance, model governance, DevOps and MLOps standards. Cross-functional Collaboration: Work closely with solution architects, data engineers, ML engineers, security teams, and business stakeholders to ensure architectural alignment and successful implementation. Platform Scalability & Performance: Define scalability patterns, performance benchmarks, and infrastructure requirements for enterprise AI platforms, including cloud-native architectures and hybrid deployment models. Risk Assessment & Compliance: Conduct architectural risk assessments, ensure compliance with enterprise security policies, data privacy regulations, and industry standards for AI systems.

Technical Leadership: Provide architectural guidance and mentorship to development teams, conduct architecture reviews, and drive adoption of architectural standards across AI initiatives. Innovation & Research: Stay current with AI platform technologies, architectural patterns, and industry trends to continuously enhance the enterprise AI architecture framework. Preferred Qualifications: Bachelors or masters degree in computer science, Information Systems, Software Engineering, or a related technical field.

Overall 15+ years of experience with at least 10 years of experience in enterprise architecture and 5+ years specifically in AI and Generative AI platform architecture, with proven success in architecting, designing and implementing enterprise grade AI platforms.

Certified TOGAF/Zachman with proven experience in applying the same Deep technical knowledge of AI/ML technologies, including machine learning frameworks, deep learning platforms, computer vision, Generative AI, Agentic Design patterns, ACP, MCP and LLMOps/ MLOps tools. Strong experience in Architecting multiple production grade AI deployments on cloud and on-premises Proven experience in multiple enterprise grade Data platform implementation. Strong experience in Data and AI governance area and responsible AI practices.

Experience in Software development models e.g. V-model Excellent stakeholder management and communication skills to effectively engage with technical teams, business leaders, and executive stakeholders.

Qualifications

BE,BTech,MS,TEch or PHD

Additional Information

Overall 15+ years of experience