Senior Manager

The Senior Manager provides senior technical and delivery leadership within Enterprise Engineering, Deployment & Operations.

The role turns architecture and product direction into executable engineering roadmaps and reusable practices that move AITO-validated and POD solutions into secure, scalable and maintainable production.

Key Accountabilities

• Own one or more team capability areas end to end, including roadmap, standards, engineering delivery, controls, service expectations and lifecycle outcomes.
• Lead and govern enterprise solution architecture and production engineering, ensuring applications, integrations, data services and AI-enabled products conform to enterprise and China AI platform reference architectures.
• Lead and govern enterprise engineering and product deployment , software, integration, API, automation and solution engineering; product-level CI/CD, production deployment, scale-up, application SRE, security, cost and technical observability, including AI-enabled business applications on the China AI platform.
• Lead and govern Shared, deployable engineering pool , integrating internal engineers, PIC, systems integrators and contractors into accountable POD and product teams.
• Lead and govern product and application Run & BAU , incidents, releases, access, service performance, operational readiness and business communications , and own the production-readiness and go-live gate, following completion of the AI platform technical qualification gate where applicable.
• Lead and govern Vendor management , China-compliant local vendors, solution delivery contracts and compliant contracting execution.
• Lead complex POD engineering, resolve technical dependencies and ensure a clean transition from AITO-validated MVP into production and BAU.
• Coordinate internal engineers, PIC, systems integrators and contingent resources as one delivery team, and mentor Managers and engineers.

Required Capabilities & Competencies (a) Critical Capabilities & Qualifications

• Enterprise engineering across software, integration, API, automation and solution engineering, and enterprise and solution architecture.
• Reusable patterns, code and design quality, automated testing, scalability, resilience, maintainability and technical debt.
• DevSecOps, CI/CD, product deployment, SRE, security, cost and technical observability, Run and BAU, and vendor and systems integrator management.
• Bachelor’s degree or above in Computer Science, Software Engineering, Information Technology, Engineering or a related computing discipline.
• 10+ years of progressive relevant experience based on a bachelor’s degree, where a master’s or doctoral degree may reduce the years required, with scope and judgment consistent with this role.
• Demonstrated ability to work across business, product, technology, data and governance stakeholders in a matrixed environment.
• Experience in the pharmaceutical or another highly regulated industry, and the China technology, data, privacy or vendor environment, is preferred.

(b) Leadership Expectations

• Outcome ownership: connects decisions to measurable business, user, service and transformation outcomes.
• AI-first and enterprise-minded: applies responsible AI, reuse, architecture, security, privacy and scale principles appropriate to the work.
• POD collaboration: enables clear accountability, effective cross-functional execution and minimal handoff friction across Business Units, GTMx, GCA, CE, AITO, PIC and peer D&T capabilities.
• Precision and learning: communicates clearly, documents decisions, uses evidence and telemetry and continuously improves delivery.

Key Collaboration

• It delivers within the platform standards and AI platform technical qualification requirements owned by AITO AI Platform & Foundation; owns solution and application architecture, product deployment, production readiness and go-live; works with Data Engineering & Semantics on production data integration; engages Business Units, GTMx, GCA and CE; and works with global engineering teams, governance functions, vendors and systems integrators.

Measures of Success

• Predictable transition from validated MVP to compliant production and scale, with a named BAU owner for every scaled product.
• Improved engineering quality, reuse, automated testing, reliability, performance and maintainability.
• Lower delivery friction and clearer accountability across internal teams, PIC and partners.
• Reliable Run & BAU with transparent risks, technical debt, cost and service-health measures.