Solution Architect - Enterprise AI

Job Title - Solution Architect - Enterprise AI

Location: Kharadi, Pune, India.

Life Unlimited. At Smith+Nephew, we design and manufacture technology that takes the limits off living.

Smith+Nephew is seeking a Solution Architect - Enterprise AI to design scalable, secure, and business-ready AI solutions that improve decision-making, productivity, and user experience across Manufacturing, MedTech, Commercial, and Procurement domains.

This role will focus on enterprise AI solution architecture, GenAI-enabled business capabilities, reusable AI design patterns, integration with ERP, commercial, procurement, manufacturing, data, analytics, and collaboration platforms, and responsible delivery of AI products in regulated MedTech environments.

The Solution Architect will partner with business stakeholders, product owners, enterprise architecture, data and analytics teams, cybersecurity, legal, compliance, delivery teams, and external vendors to translate business needs into practical Enterprise AI solutions. The role will support the full IT project lifecycle, provide AI design assurance, guide responsible AI adoption, and help shape "coach on the shoulder" initiatives that embed contextual guidance, automation, and intelligent assistance into business workflows.

What will you be doing?

Enterprise AI Solution Design & Architecture Patterns

Design Enterprise AI and GenAI solutions that are scalable, secure, user-centric, and aligned to business outcomes across Manufacturing, MedTech, Commercial, and Procurement domains.

Create AI solution blueprints, reference architectures, reusable design patterns, data flow views, integration approaches, and delivery-ready architecture documentation.

Translate business opportunities into practical AI-enabled capabilities, including intelligent assistants, knowledge discovery, workflow automation, insight generation, and decision support.

Identify solution risks, data dependencies, model limitations, non-functional requirements, adoption considerations, and options for reuse, simplification, and long-term maintainability.

AI Platform Integration & Enterprise System Connectivity

Define integration designs connecting AI solutions with ERP, CRM, procurement, manufacturing, quality, regulatory, data, analytics, document management, workflow, and collaboration platforms.

Apply API-led, event-driven, retrieval-augmented generation, orchestration, workflow automation, knowledge graph, and secure data access patterns based on business criticality and user needs.

Ensure AI solutions are designed for security, privacy, resilience, scalability, observability, auditability, explain ability, and operational support.

Work with platform, data, and vendor teams to validate integration specifications, data access controls, model interaction patterns, testing needs, and support handover requirements.

AI Delivery Lifecycle, Governance & Design Assurance

Provide solution architecture leadership across the AI delivery lifecycle, from opportunity discovery and use-case shaping through design, build, validation, deployment, adoption, monitoring, and continuous improvement.

Lead AI design workshops, solution walkthroughs, architecture reviews, governance forums, risk assessments, and technical issue resolution with business, IT, data, security, compliance, and vendor teams.

Maintain architecture decisions, AI use-case assumptions, data lineage considerations, model constraints, risks, dependencies, validation needs, and traceability between business outcomes and delivered capabilities.

Ensure AI solutions meet business outcomes, responsible AI expectations, regulatory needs, cybersecurity controls, privacy requirements, and operational readiness criteria.

Business Domain Enablement: Manufacturing, MedTech, Commercial & Procurement

Apply strong understanding of Manufacturing and MedTech business processes, regulated operations, product quality, supply chain, and compliance-aware delivery to shape relevant AI solutions.

Bring experience in Commercial and Procurement domains, including sales operations, customer engagement, pricing, contracting, sourcing, supplier management, purchasing, and spend analytics.

Partner with functional leaders to identify AI opportunities that improve productivity, decision quality, process consistency, knowledge access, compliance readiness, and end-user adoption.

Support discovery, prioritization, solution fit assessment, value case development, and roadmap alignment for AI use cases across global and regional business functions.

Coach on the Shoulder AI Adoption Initiatives

Design and enable coach on the shoulder experiences that provide contextual guidance, next-best-action recommendations, knowledge support, and embedded assistance within business workflows.

Shape AI assistant experiences for commercial teams, procurement users, manufacturing operations, service teams, and knowledge workers by combining user journeys, process context, trusted data, and enterprise controls.

Support prompt design, knowledge grounding, human-in-the-loop review, feedback capture, guardrails, adoption measurement, and continuous improvement of AI-enabled user experiences.

Promote user trust, transparency, change adoption, and measurable productivity outcomes through clear solution design and close partnership with business change teams.

Vendor-Led Delivery & Stakeholder Collaboration

Produce clear architecture deliverables, AI solution design documents, integration inventories, pattern guidance, decision logs, risk registers, and delivery-ready design packs.

Collaborate with project managers, product owners, business analysts, data scientists, engineers, developers, testers, cybersecurity, compliance, operations teams, and vendors to remove blockers and maintain design integrity.

Lead solution architecture activities for vendor-led AI delivery programs, ensuring partner outputs align with enterprise standards, responsible AI expectations, security controls, and business scope.

Communicate AI solution options, risks, trade-offs, adoption considerations, and recommendations clearly to senior stakeholders and delivery governance forums.

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 : Azure AI Engineer, Azure Solutions Architect, Microsoft Copilot, Responsible AI, Data & AI, Cloud Architecture, TOGAF, Agile, PMP, or equivalent certifications preferred.
• •Experience: 10+ years of experience in Solution Architecture , enterprise applications, data and analytics, AI-enabled solutions, systems integration , or complex IT program delivery roles.
• •Experience designing Enterprise AI, GenAI, intelligent automation , analytics, digital assistant , or workflow augmentation solutions in an enterprise environment.
• •Strong understanding of Manufacturing and MedTech domains, including regulated processes, quality, supply chain, manufacturing operations, compliance, validation-aware delivery, and operational risk.
• •Experience in Commercial and Procurement functions is preferred, including sales operations, customer engagement, contracting, sourcing, supplier management, purchasing, and spend/process analytics.
• •Proven experience designing integrations across ERP, CRM, procurement, manufacturi