Product Architect – Senior Manager

As a Product Architect Senior Manager you will be a hands‑on, full stack technology leader to serve as the onshore engineering counterpart to our Product Manager, helping drive the development of innovative, custom AI‑powered products for the pharmaceutical industry. Our products are built on AWS and integrate deeply with the marketing and content technology that pharma commercial teams rely on, especially Adobe and Salesforce.

They are delivered to large global pharma clients and designed to scale to new ones. The core mandate is to drive a fundamentally new way of working: an AI‑first development mindset where models and agents are applied to how we build, test, and deploy, not just to what we build. Testing is central to this. AI‑generated tests, automated evaluation of AI output against validated ground truth, and continuous regression checks should be standard parts of the development cycle, not afterthoughts.

This leader will guide and coach an offshore team spanning data science, full stack engineering, QA and testing, and Dev Ops, helping them rethink their day‑to‑day work through that lens. Lead data and analytics efforts within our Data and Analytics practice, focusing on Adobe initiatives that use advanced analysis, data manipulation, visualization, and statistical modeling to support client decision‑making. As a Senior Manager you will lead complex work streams, apply sound judgment in ambiguous situations, and guide teams through strategic problem solving while building trusted relationships across stakeholders.

In this role at PwC, you will shape how data is used to identify insights, support operational improvements, and translate findings into clear actions for client teams. As a Senior Manager you will lead complex work streams, apply sound judgment in ambiguous situations, and guide teams through strategic problem solving while building trusted relationships across stakeholders. In this role at PwC, you will shape how data is used to identify insights, support operational improvements, and translate findings into clear actions for client teams.

• Act as the onshore technical owner for the product portfolio, partnering with the Product Manager on roadmap, scope, feasibility, and delivery tradeoffs.
• Set and champion an AI‑first engineering operating model where agentic development, AI‑assisted testing, automated evaluation, and AI‑supported deployment are the defaults rather than experiments.
• Establish a testing and quality strategy suited to AI products, including test‑driven development, evaluation gates for AI accuracy, and regression coverage across integrations.
• Make validated ground truth a release gate, partnering with SMEs on gold sets and accuracy thresholds.
• Manage the LLMOps practices in production, including monitoring model performance and output quality, managing token usage and cost, and planning safe model version upgrades.
• Evaluate new models and AI capabilities against our benchmarks and recommend what to adopt for client delivery.
• Embed secure‑by‑design practices across the development lifecycle and lead the team through client security reviews, data protection requirements, and access control standards.
• Design AI output for auditability, including cited evidence, model and prompt traceability, and human review.
• Lead, mentor, and raise the bar for an offshore team across data science, full stack, QA, and Dev Ops, bridging time zones and creating clear handoff – Responsible technical architecture decisions, including what belongs in the reusable platform and what should stay as client‑specific configuration as products scale to new clients.
• Hands‑on: review code, prototype, and unblock the team on hard technical…