Scaled AI & Solution Architect

Pfizer; India; On-site; INR 700,000 - 1,200,000; Full time

Job summary

Pfizer in India seeks a Scaled AI & Solution Architect to be the senior technical design authority for Digital Quality. You will set AI and solution architecture direction across the DQ portfolio, defining target architectures, reusable components and engineering standards for global impact.

You will champion scaled AI adoption, guide governance, and mentor teams to ensure compliant, production-grade solutions across Quality, Safety and Environmental Operations.

Qualifications

• Bachelor's degree required in IT, Engineering, Environmental or Occupational Health sciences or related field.
• 10+ years in solution architecture, technical leadership or enterprise software delivery.

Responsibilities

• Own the target-state solution architecture for the Digital Quality portfolio across quality, lab, manufacturing quality, safety and environment.
• Define how products, platforms, data and integrations fit, driving convergence onto a common architecture.
• Publish and maintain architecture standards, reference patterns, reusable components and guardrails.
• Lead scaled AI enablement and define AI architecture with lifecycle governance.
• Review designs at lifecycle gates and advise on build-vs-buy, platform selection and vendor fit.
• Mentor architects and engineers, spreading best practices across DQ and Digital.
• Ensure GxP compliance, data integrity and cyber security by design.
• Evaluate emerging AI/tech and translate experiments into scalable production capability.

Skills

Solution architecture

AI architecture

Technical leadership

Cross-functional collaboration

Education

Bachelor's degree in IT/Engineering

Job description

ROLE SUMMARY

The Scaled AI & Solution Architect is the senior technical design authority for the Digital Quality (DQ) organisation, which delivers the solutions that transform Quality, Safety and Environmental Operations (QSEO) across Pfizer. The role is a global individual contributor position accountable for setting and driving the AI and solution architecture direction across the entire DQ product portfolio, rather than for the delivery of any single product.

The incumbent defines the target architecture, reference patterns, reusable components and engineering standards that every DQ solution is built against, so that capability is built once and reused many times rather than rebuilt product by product. The role leads the scaled adoption of artificial intelligence (AI) and agentic AI across the portfolio, translating enterprise AI platforms and emerging technology into GxP-compliant, validated, production-grade capability that measurably improves quality, safety and environmental outcomes at site level.

Recognised as an expert within and beyond Digital Quality, the incumbent influences the strategic technology direction of the QSEO business, and partners with Solution Leads, the Platform and Solution Engineering team, Enterprise Architecture, Cyber Security to ensure architectural coherence, compliance and pace across a complex global portfolio.

ROLE RESPONSIBILITIES

• Cross-Product Solution Architecture Own the target-state solution architecture for the Digital Quality portfolio, spanning quality management, laboratory, manufacturing quality, and safety, environment and occupational health solutions.
• Define how products, platforms, data and integrations fit together, and drive convergence of point solutions onto common architecture, avoiding duplicated capability and unmanaged technical debt across the portfolio.
• Architecture Standards, Patterns and Reusable Components Establish, publish and maintain the architecture standards, reference patterns, reusable components and engineering guardrails that DQ solutions are designed and built against, covering integration, data, identity, AI, validation and cyber security.
• Make reuse the path of least resistance for delivery teams, and measure adoption, reuse and the resulting delivery efficiency.
• Scaled AI Enablement Define and drive the AI and agentic AI architecture for the DQ portfolio, including use case patterns such as deviation and incident triage, leading-indicator prediction, automated document and content generation, and conversational access to standards and procedures.
• Determine where AI capability should be built once as a shared service versus configured per product, and ensure AI is delivered on enterprise platforms with appropriate human oversight, evaluation, model monitoring and lifecycle management.
• Design Authority and Technical Governance Act as design authority for significant DQ investments, reviewing and approving solution designs at key lifecycle gates and providing architectural assurance on build-versus-buy, platform selection and vendor technical fit.
• Identify multiple viable options for highly complex problems, set out the trade-offs in cost, risk, compliance and time to value, and make clear recommendations to Digital and business leadership and relevant governance forums.
• Technical Leadership and Capability Building Provide hands‑on architectural leadership to Solution Leads, Product Managers, engineers and vendor teams across the portfolio without direct reporting authority, influencing through expertise, credibility and evidence.
• Mentor and raise the technical capability of architects and engineers across Digital Quality, and lead architecture and AI Communities of Practice that spread good practice across DQ and the wider Digital organisation.
• Compliance, Data Integrity and Security by Design Ensure architectural decisions embed GxP computerised system compliance, data integrity, data privacy and cyber security requirements from the outset, in partnership with Quality, Legal, Privacy, Compliance and Cyber Security.
• Define validation‑efficient architecture patterns that allow AI and cloud capability to be deployed at pace while remaining inspection‑ready.
• Innovation and Emerging Technology Exercise foresight in evaluating emerging AI, data and platform technologies, and act independently on self‑initiated proofs of concept and technical experiments that challenge the status quo and shape the multi‑year DQ technology roadmap.
• Take appropriate, well‑governed technical risk, and translate proven experiments into scaled, supportable production capability with a defined adoption path.

QUALIFICATIONS

• Basic Qualifications Bachelor's degree required in Information Technology, Engineering, Environmental or Occupational Health Sciences, Life Sciences or a related discipline.
• 10+ years of relevant experience in in solution architecture, technical leadership or enterprise software delivery (9+ years with an MS/MBA; 7+ years with a PhD), inc