Associate Director, AI Enablement – Commercial & Medical Affairs

🕒 May 28

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BeOne Medicines

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 2010

BeOne Medicines is a global oncology company domiciled in Switzerland that is discovering and developing innovative treatments that are more affordable and accessible to cancer patients worldwide. With a portfolio spanning hematology and solid tumors, BeOne is expediting development of its diverse pipeline of novel therapeutics through its internal capabilities and collaborations. With a growing global team of more than 11,000 colleagues spanning six continents, the Company is committed to radically improving access to medicines for far more patients who need them.

📋 Description

• Lead the design and implementation of enterprise AI/ML and GenAI platforms, including RAG pipelines, LLM orchestration layers, and agentic AI frameworks. • Build scalable, reusable AI services and APIs that enable rapid development and deployment of AI use cases across the organization. • Define and implement LLMOps/MLOps practices (model lifecycle management, monitoring, evaluation, versioning, CI/CD). • Architect solutions integrating vector databases, knowledge stores, and enterprise data platforms for context-aware AI applications. • Ensure seamless integration of AI capabilities with existing data, CRM, and marketing technology ecosystems. • Establish frameworks, toolkits, and best practices to enable data scientists, engineers, and analysts to build AI-powered applications efficiently. • Drive self-service AI capabilities, including prompt frameworks, reusable components, and standardized pipelines. • Improve developer productivity and experimentation velocity through well-designed AI abstractions and tooling. • Lead internal adoption of AI platforms through documentation, training, and enablement programs. • Design and operationalize RAG architectures for enterprise knowledge retrieval and grounded generation. • Build and scale agentic AI systems capable of multi-step reasoning, orchestration, and task automation. • Evaluate and implement LLM strategies (fine-tuning vs. RAG vs. hybrid approaches) based on use case needs. • Ensure robustness of GenAI systems through evaluation frameworks, guardrails, and monitoring. • Partner with data engineering teams to ensure high-quality, accessible, and governed data pipelines for AI consumption. • Enable real-time and batch AI use cases through event-driven and streaming architectures. • Optimize performance, scalability, and cost of AI workloads across cloud environments. • Define and enforce AI governance frameworks, including model validation, explainability, and auditability. • Ensure compliance with data privacy, security, and regulatory requirements (e.g., HIPAA, GDPR, GxP where applicable). • Implement safeguards for GenAI risks (hallucination, bias, data leakage). • Act as a bridge between technology, data science, and business teams, enabling scalable AI adoption. • Partner with stakeholders to translate business needs into platform capabilities and reusable solutions (not one-off builds).

🎯 Requirements

• Master's degree or higher with 6+ years of experience in AI/ML engineering, platform development, or data engineering, preferably in enterprise environments. • Strong hands-on experience with: RAG architectures and LLM frameworks (e.g., LangChain, LlamaIndex) • Vector databases (Pinecone, FAISS, Weaviate, etc.) • LLMOps/MLOps tooling and production model lifecycle management • Experience building scalable AI platforms, APIs, and microservices architectures. • Proficiency in Python, SQL, and modern cloud platforms (AWS, Azure, or GCP). • Experience with Databricks, Snowflake, or similar data platforms. • Familiarity with distributed systems, real-time architectures, and data pipelines. • Strong understanding of AI system evaluation, monitoring, and optimization. • Proven experience leading platform-centric AI initiatives, not just analytics use cases. • Ability to drive standardization, reuse, and scalability across AI implementations. • Strong collaboration skills across engineering, data science, and business teams. • Experience influencing architecture decisions and driving adoption of shared platforms. • Ability to translate complex AI insights into clear, strategic recommendations for business leaders. • Strong influencing skills, collaborating effectively with stakeholders, and cross-functional teams. • Experience leading AI/analytics initiatives that drive measurable business impact. • Excellent communication and storytelling skills, making AI-driven insights accessible and actionable for executives.

🏖️ Benefits

• Medical • Dental • Vision • 401(k) • FSA/HSA • Life Insurance • Paid Time Off • Wellness