Enterprise Architect - Enterprise AI Platform & Governance

Job Title - Enterprise Architect - Enterprise AI Platform & Governance

This role will serve as the central architecture authority for Artificial Intelligence initiatives across the organisation, defining enterprise AI standards, Agent-to-Agent (A2A) communication patterns, Model Context Protocol (MCP) frameworks, integration architectures, security controls and enterprise deployment guidelines.

The role will partner with business leaders, digital transformation teams, platform owners, cybersecurity, data teams and external technology partners to establish scalable, secure, compliant and reusable AI solutions. It will participate in the Architecture Review Board (ARB), govern AI technology decisions, lead platform evaluations and selection scoring, and provide templates, playbooks, reference architectures and roadmaps to accelerate enterprise AI adoption.

• Define enterprise AI architecture vision, principles, standards, reference architectures and target-state roadmap.

• Create enterprise-grade patterns for Generative AI, Agentic AI, RAG, orchestration, model integration and AI operations.

• Align AI strategy with cloud, data, cybersecurity, integration, enterprise architecture and digital transformation strategies.

• Provide guidance for enterprise deployments, including pilots, scale-up, lifecycle management and adoption governance.

• Serve as the AI architecture authority in the ARB and provide design assurance for AI programmes.

• Define AI governance guardrails covering architecture, security, privacy, validation, compliance, responsible AI, monitoring and operational controls.

• Review AI solution designs to ensure alignment with enterprise standards, regulatory expectations and scalable deployment practices.

• Publish standards, reusable templates, checklists, decision records and architecture review packs for AI initiatives.

• Define enterprise standards for AI agent architecture, autonomous workflows and multi-agent orchestration.

• Establish patterns for Agent-to-Agent communication, agent collaboration, ownership, security, observability and lifecycle management.

• Define enterprise adoption guidance for MCP, context brokering, tool integration, memory, retrieval and interoperability standards.

• Create reusable agent blueprints and integration patterns for enterprise systems and business processes.

• Lead AI platform assessments, proofs of concept, vendor evaluations and technology comparison exercises.

• Develop scoring frameworks and objective evaluation criteria for AI platform selection decisions.

• Assess GenAI, LLM, agentic AI, vector database, orchestration, prompt/model management, monitoring and AI engineering platforms.

• Recommend strategic platform investments based on architectural fit, scalability, security, compliance, cost, integration and enterprise readiness.

• Define integration standards connecting AI platforms with ERP, CRM, HR, Supply Chain, Quality, Regulatory, Data Lake, Analytics and enterprise applications.

• Establish API-led, event-driven, service-oriented and agent-enabled integration patterns.

• Govern data access patterns, semantic layers, retrieval frameworks, model connectors, observability and secure consumption of enterprise data.

• Ensure resilience, scalability, performance, security and auditability across AI integrations.

• Provide architecture templates, reference designs, standards, playbooks, scorecards and roadmap artifacts for AI programmes.

• Mentor solution architects, engineering teams, delivery leads and partners on enterprise AI best practices.

• Support AI portfolio planning, sequencing, dependency management and delivery governance.

• Drive global consistency and reuse across AI initiatives while enabling business agility.

• Exercises sound judgment and makes clear, timely decisions in ambiguous or evolving situations

• Applies critical thinking to interpret complex information, make sense of ambiguity, and guide clear action

• Demonstrates ethical reasoning and accountability in decision-making and delivery

• Brings creativity and strategic imagination to reframe problems, explore opportunities, and shape new solutions

• Shows learning agility and adaptability in response to change, feedback, and new information.

• Education: Bachelor’s degree in computer science, Engineering, Information Systems or equivalent experience.
• Licenses / Certifications: TOGAF, Azure AI, Azure Solutions Architect, Cloud Architecture, AI/ML Architecture or equivalent certifications preferred.
• Experience: 12+ years of experience in Enterprise Architecture, Solution Architecture, Technology Strategy or related leadership roles.
• 5+ years of experience leading large-scale Enterprise AI, Generative AI, Agentic AI or digital transformation initiatives.
• Proven experience defining AI standards, architecture governance, technology roadmaps and reference architectures for global enterprises.
• Hands-on experience with cloud AI platforms such as Azure AI, OpenAI, Microsoft Copilot ecosystem, AWS AI, Google AI or equivalent platforms.
• Strong experience with enterprise integration, data platforms, ERP/CRM ecosystems, security architecture and operational governance.
• Experience participating in Architecture Review Boards and leading platform evaluation or selection decisions.
• Experience in manufacturing and MedTech domains, including regulated product environments, quality management, supply chain, manufacturing operations and compliance-driven technology delivery.
• Experience with SAP S/4HANA transformation, integration and enterprise architecture, including ERP modernization, process standardization, data integration and AI-enabled business process automation.
• Core Competencies:
• Enterprise Architecture frameworks such as TOGAF or equivalent; business capability modelling; technology strategy and roadmap planning.
• Generative AI, LLMs, RAG, vector databases, semantic search, AI agents, multi-agent orchestration, MCP and A2A standards.
• API-led, event-driven, microservices, cloud-native and enterprise integration architecture.
• Responsible AI, AI security, privacy, auditability, model governance, validation, observability and AI operations.
• Executive stakeholder engagement, technology decision-making, influencing without authority, architecture governance and mentoring.

We believe in crafting the greatest good for society. Our strongest investments are in our people and the patients we serve.

• Your Future: Major Medical coverage + Policy exclusions and insurance non-medical limit. Educational Assistance.
• Work/Life Balance: Flexible Personal/Vacation Time Off, Privilege Leave, Floater Leave.
• Your Wellbeing: Parents / Parents in Law’s Insurance, Employee Assistance Program, Parental Leave.
• Flexibility: Hybrid Work Model (For most professional roles)
• Training: Hands-On, Team-Customized, Mentorship
• Extra Perks: Free Cab Transport facility for all employees, One Time Meal provided to all employees as per shift. Night Shift Allowances.