Senior Director, Engineering

SUMMARY This role owns the engineering build accountability for the Medical Affairs Digital and AI portfolio.  This role leads the team that turns solution architecture and product requirements into shipped, production-grade AI systems at enterprise scale. It carries direct people-leadership accountability for a build team of three Build Engineers and a Data Integration Engineer, and hands-on technical accountability for engineering standards, delivery velocity, and production reliability across Medical Affairs globally. This is a peer role to the Senior Director, Solution Architecture and the Senior Director, Product Management — and works closely together with these peers to deliver enterprise scale solutions -- product management defines what gets built and why, architecture defines how a solution is built and engineering builds and ships it.   This role drives engineering standards, build quality, and delivery discipline that ensures reliability and speed for every AI system deployed to production. The Senior Director operates with significant technical and managerial autonomy, translating architecture blueprints and product roadmaps into committed delivery plans, and is accountable for realistic delivery commitments, production reliability, and engineering risk — including the technical debt, security, and compliance consequences of build decisions. The Senior Director, Engineering leads and builds the engineering organization responsible for constructing, integrating, and shipping Medical Affairs' AI-powered products and platforms. This is a hands-on technical leadership role owning software engineering practice, data integration execution, CI/CD and LLMOps/MLOps discipline, and production reliability for the portfolio of Medical Affairs Tier 1 Agentic AI and LLM-based systems. Reporting into the lead of Medical AI Acceleration and Delivery and partnering with peer Senior Directors of Solution Architecture and Product Management, this leader turns architecture and product intent into working, tested, deployed software — while building, coaching, and retaining an engineering team capable of operating at enterprise AI scale.

RESPONSIBILITIES Engineering Strategy & Delivery Leadership Own end-to-end engineering delivery for the Medical AI Acceleration portfolio, translating solution architecture and product requirements into working, production-grade software. Set engineering standards, coding practices, and technical quality bars across the build team, ensuring consistency, maintainability, and reuse across products. Establish and continuously improve CI/CD pipelines, environment strategy, and release management practice across AI/ML and traditional software components. Own sprint and iteration execution in partnership with the Scrum Master, ensuring committed work is delivered on time and to standard. AI/ML Build & Data Integration Direct the build of Agentic AI systems, LLM integrations, and RAG pipelines, translating architectural design into deployed, functioning services. Oversee data integration engineering across core enterprise systems (e.g., Veeva CRM, PromoMats, Salesforce Life Sciences/Marketing Cloud), ensuring reliable, well-governed data pipelines feed AI and analytics platforms. Implement and maintain LLMOps/MLOps practice — model deployment pipelines, monitoring, retraining triggers, and performance measurement — in partnership with Solution Architecture. Ensure engineering-level enforcement of responsible AI safeguards (data access controls, prompt injection defenses, model output monitoring) defined by the architecture function. Technical Quality, Reliability & Risk Management Own production reliability, uptime, and incident response for the Medical AI Acceleration portfolio's shipped systems. Partner with Security, Compliance, and Solution Architecture to ensure engineering practice meets regulatory requirements (GxP, HIPAA, GDPR) and passes required technical gates before