Enterprise Architect - Enterprise AI Platform & Governance
smithnephew · IND - NonGBS-Pune-Kharadi · India · On-site
Posted Oct 5, 2026
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Job Title - Enterprise Architect - Enterprise AI Platform & Governance
Location: Kharadi, Pune, India.
Life Unlimited. At Smith+Nephew, we design and manufacture technology that takes the limits off living.
Smith+Nephew is seeking an Enterprise Architect - Enterprise AI Platform & Governance to lead the enterprise-wide AI architecture strategy, governance, standards and adoption roadmap.
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.
What will you be doing?
Enterprise AI Architecture & Strategy
• 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.
AI Governance & Architecture Review Board
• 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.
Agent Architecture, MCP & A2A Standards
• 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.
Enterprise AI Platform Selection & Technology Evaluation
• Lead AI platform assessments, proofs of concept, vendor evaluations and technology…