Enterprise Architect - AI Platform and Governance

Smith & Nephew Healthcare; Pune District; Vor Ort; INR 3.500.000 - 5.200.000; Vollzeit

Zusammenfassung

Smith+ Nephew in Pune, India seeks an Enterprise Architect for Enterprise AI Platform & Governance to lead AI architecture strategy, governance and adoption roadmaps. Collaborate with business leaders, cybersecurity, data teams and platform owners to establish scalable, secure AI solutions and enterprise deployment guidelines.

You will drive AI patterns, agent-to-agent communication, MCP frameworks and integration architectures while supporting ARB governance and platform evaluations for

Qualifikationen

• Extensive enterprise AI architecture and governance experience.
• Proven track record in AI strategy, standards and adoption roadmaps.
• Leadership in ARB governance and platform evaluation.
• Hands-on with cloud AI platforms and enterprise integration.
• Strong stakeholder management across business, security and data teams.

Aufgaben

• Define enterprise AI architecture vision, standards and reference architectures.
• Lead AI platform assessments, proofs of concept and vendor evaluations.
• Govern AI deployment patterns, security, privacy and compliance.
• Develop MCP, A2A and integration patterns across ERP/CRM/data layers.

Kenntnisse

Decision making

Critical thinking

Ethical reasoning

Creativity

Learning agility

Ausbildung

Bachelor's degree in Computer Science / Engineering / Information Systems

TOGAF Certification

Azure AI Certification / Azure Solutions Architect Certification

Tools

Azure AI

OpenAI

Microsoft Copilot

AWS AI

Google AI

Jobbeschreibung

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?

• 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 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.

AI Integration Architecture

• 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.

Enterprise AI Delivery Enablement

• 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.

Skills: Mindset & Behaviors:

• 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.

What will you need to be successful?

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.

Experience: 5+ years of experience leading large-scale Enterprise AI, Generative AI, Agentic AI or digital transformation initiatives.

Experience: Proven experience defining AI standards, architecture governance, technology roadmaps and reference architectures for global enterprises.

Experience: Hands-on experience with cloud AI platforms such as Azure AI, OpenAI, Microsoft Copilot ecosystem, AWS AI, Google AI or equivalent platforms.

Experience: Strong experience with enterprise integration, data platforms, ERP/CRM ecosystems, security architecture and operational governance.

Experience: Experience participating in Architecture Review Boards and leading platform evaluation or selection decisions.

Experience: Experience in manufacturing and MedTech domains, including regulated product environments, quality management, supply chain, manufacturing operations and compliance‑driven technology delivery.

Experience: 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.

Inclusion + Belonging - Committed to Welcoming, Celebrating and Thriving.

Learn more about our Employee Inclusion Groups on our website https://www.smith-nephew.com/

Other reasons why you will love it here! 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.

Experience Level Senior Level