Product Architect – Senior Manager

PricewaterhouseCoopers•Los Angeles, NY

About The Position

As a Product Architect Senior Manager, you will be a hands-on, full-stack technology leader and the onshore engineering counterpart to the Product Manager. You will help develop innovative, custom AI-powered products for the pharmaceutical industry. Products are built on AWS, integrate with marketing and content technologies used by pharma commercial teams—especially Adobe and Salesforce—and are delivered to large global pharma clients with the aim of scaling to additional clients. The role drives an AI-first development approach, applying models and agents to how products are built, tested, and deployed. Testing is central: AI-generated tests, automated evaluation against validated ground truth, and continuous regression checks are expected parts of the development cycle. You will lead and coach an offshore team across data science, full-stack engineering, QA and testing, and DevOps. You will also lead data and analytics work within PwC’s Data and Analytics practice, focusing on Adobe initiatives and using analysis, data manipulation, visualization, and statistical modeling to support client decisions. As a Senior Manager, you will lead complex workstreams, use judgment in ambiguous situations, guide strategic problem solving, and build stakeholder relationships. You will help clients use data to identify insights, improve operations, and turn findings into clear actions. Travel requirements are up to 40%. The salary range is $124,000–$280,000, with actual compensation dependent on skills, experience, qualifications, location, and applicable employment laws. Hired individuals are eligible for an annual discretionary bonus.

Requirements

At least a Bachelor's degree.
At least 7 years of experience.

Nice To Haves

Preferred field of study: Accounting, Engineering, Data Processing/Analytics/Science, Computer and Information Science, Economics, or Finance.
At least one certification in databases (Databricks or MS SQL), visualization tools (Power BI), cloud platforms (AWS, Azure, or GCP), or predictive modeling/ML (Python or SAS).
Senior-level client advisory experience across Adobe transformation programs.
Ability to apply systems thinking to complex data, analytics, and AI challenges.
Ability to craft clear executive messaging that tells a holistic story.
Ability to coach diverse teams through ambiguity while driving decisions.

Responsibilities

Serve as the onshore technical owner for the product portfolio and partner with the Product Manager on roadmap, scope, feasibility, and delivery tradeoffs.
Establish and champion an AI-first engineering operating model, using agentic development, AI-assisted testing, automated evaluation, and AI-supported deployment as standard practices.
Establish testing and quality strategies for AI products, including test-driven development, AI-accuracy evaluation gates, and regression coverage across integrations.
Partner with subject-matter experts to establish validated ground-truth gold sets and accuracy thresholds as release gates.
Manage production LLMOps practices, including monitoring model performance and output quality, managing token usage and cost, and planning safe model-version upgrades.
Evaluate models and AI capabilities against benchmarks and recommend which to adopt for client delivery.
Embed secure-by-design practices throughout development and guide teams through client security reviews, data-protection requirements, and access-control standards.
Design AI outputs for auditability through cited evidence, model and prompt traceability, and human review.
Lead, mentor, and develop an offshore team spanning data science, full-stack engineering, QA, and DevOps; bridge time zones and establish clear handoffs.
Make technical architecture decisions, including determining what belongs in the reusable platform versus client-specific configuration as products scale.
Review code, prototype, and unblock the team on difficult technical problems.
Partner with client technology stakeholders, including IT, integration, and security teams, on integrations, environments, and sign-offs.
Represent engineering in client conversations and explain technical capabilities in terms of business value.
Lead workstreams that use data analysis to uncover insights, shape decisions, and support client goals.
Design and deliver analytics solutions using Adobe platforms, SQL, Python, Power BI, Tableau, and related data tools.
Translate business questions into measurement strategies, KPI frameworks, and reporting approaches that guide action.
Build data pipelines, prepare datasets, and validate data quality for accurate analysis and visualization.
Apply statistical modeling, predictive analytics, and scenario analysis to identify trends, opportunities, and risks.
Advise client stakeholders on analytics approaches, interpret findings, and present clear recommendations.
Coach team members through complex delivery tasks while driving progress across multiple workstreams.
Collaborate across marketing and commerce technology efforts to align analytics outputs with broader transformation objectives.