Director of AI Engineering

We are seeking an experienced Director of AI Engineering to lead our AI and software engineering platform initiatives. This senior leadership role requires a minimum of 15 years of software engineering experience, with at least 5 years in senior engineering leadership positions (Senior Director/Director). You will be responsible for leading leaders across complex, multi-product engineering organizations. A strong technical foundation across the full software stack, including cloud-native, distributed, and data-intensive systems, is essential. Proven success in delivering production-grade Generative AI and Agentic AI solutions is crucial, encompassing LLM-powered applications, agentic workflows, model integration, evaluation, lifecycle management, and MLOps/LLMOps practices. You should have experience collaborating with Data Science and AI Research teams to scale AI solutions. Prior experience in product-focused software companies is highly valued, along with excellent executive communication and stakeholder management skills.

Key Responsibilities:

• AI & Software Engineering Platform Leadership: Define and execute engineering strategy for data and software platforms supporting AI-driven products, focusing on AI-first architectures, LLM services, agentic workflows, and human-in-the-loop systems. Build robust data and software foundations for advanced analytics, AI inference, and real-time decisioning at scale. Collaborate with Data Science, AI Research, and Architecture teams to operationalize AI models into reliable, compliant, and enterprise-grade production systems. Establish platform capabilities for prompt management, model evaluation, observability, governance, and responsible AI.
• Organizational & Engineering Leadership: Lead and scale multiple Director- and Senior Manager-led engineering organizations responsible for both AI-enabled and core product capabilities. Set clear expectations for end-to-end ownership across full-stack, data, and AI-enabled engineering teams. Balance rapid AI innovation with enterprise-grade standards for reliability, security, performance, and maintainability.
• Technical & Platform Strategy: Influence and define enterprise standards for software engineering excellence and AI-enabled development, including architecture, coding, testing, CI/CD, DevOps/SRE, MLOps, LLMOps, and agent lifecycle management. Ensure platforms are cloud-native, scalable, secure, and compliant with data privacy, regulatory, and governance requirements. Drive the adoption of AI-assisted development tools to boost engineering productivity and quality.
• Product & Business Partnership: Serve as a senior technology partner to Product and Business leaders within Market Access and LS&H portfolios. Translate complex business and customer challenges into scalable data, software, and AI solutions with measurable commercial and customer impact. Guide prioritization by balancing innovation, technical debt, feasibility, risk, cost, and time-to-market.
• People, Culture & Talent: Build, mentor, and retain a strong leadership bench of Directors and Senior Managers with expertise in product engineering, data platforms, and AI-enabled systems. Shape hiring strategies to attract top-tier Full Stack, Data, and AI Platform engineering talent. Foster a culture of engineering excellence, accountability, continuous learning, and responsible innovation.
• Operational Excellence & Governance: Establish key metrics and governance across software, data, and AI platforms, covering quality, reliability, cost, performance, security, and business impact. Mitigate operational risks through disciplined engineering practices, robust observability, and continuous improvement. Partner with Security, Legal, Compliance, and Privacy teams to ensure responsible, ethical, and compliant AI deployment.

Preferred Qualifications:

• Experience building data and AI platforms using proprietary and third-party datasets in regulated environments.
• Background in Life Sciences & Healthcare or other highly data-intensive, regulated domains.
• Experience with responsible AI, data governance, and compliance frameworks.
• Proven track record of driving enterprise-scale software engineering or AI transformation initiatives.