Product Engineering Manager - Commercial Pharma US Targeting, Recommendation, Optimization and Measurement
Genentech · South San Francisco, CA · Business Strategy & Delivery
About this role
Genentech is hiring a mid-level Engineering Manager in the software engineering function based in South San Francisco, CA. The posting calls out experience with Agile, Data Visualization, Machine Learning. Compensation is listed at $149,700–$278,100 per year.
- Role
- Engineering Manager
- Function
- software engineering
- Level
- mid
- Track
- hybrid
- Employment
- Full-time
- Location
- South San Francisco, CA
- Department
- Business Strategy & Delivery
- Posted
- Apr 2, 2026
More roles at Genentech
Job description
from Genentech careersThe Position
Product Engineering Manager - Commercial Pharma US Targeting, Recommendation, Optimization and Measurement
Roche Digital Technology (RDT) is where innovation meets purpose. As a global team at the heart of Roche, we are a community of business-minded technologists committed to help shape tomorrow’s digital future of healthcare. Our mission is to power Roche through cutting-edge digital technologies, harnessing the potential of artificial intelligence, data, and scalable tech innovations. Driven by purpose and passion, we’re building a future where digital is a core strength across all of Roche, enabling smarter ways of working, unlocking human potential, and driving breakthroughs that truly matter for millions of patients around the world.
The Opportunity
As a Product Engineering Manager of Commercial Pharma US Targeting, Recommendation, Optimization and Measurement, you will sit at the intersection of cutting-edge technology and life-changing medicine.
You will lead a team responsible for architecting scalable digital solutions that transform commercial intent into business impact while fostering a high-performing, sustainable engineering culture. This role partners closely with the Genentech business product owners that support key business commercial functions of measurement (e.g., segmenting HCPs, dynamic lists, geospatial analysis etc.), recommendation (e.g., Next Best Action), optimization (e.g., measurable ROI, “what-if” simulations etc.) and Measurement (e.g., Attribution modeling, operational health etc.).