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Associate Director, AI Enablement – Commercial & Medical Affairs
BeOne MedicinesAssociate Director, AI Enablement at BeOne leading enterprise AI platforms and capabilities. Focusing on engineering and operationalizing AI systems for commercial and medical applications.
Tech Stack
Tools & technologiesAWSAzureCloudDistributed SystemsGoogle Cloud PlatformMicroservicesPythonSQL
About the role
Key responsibilities & impact- 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
What you’ll need- 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
Comp & perks- Medical
- Dental
- Vision
- 401(k)
- FSA/HSA
- Life Insurance
- Paid Time Off
- Wellness
ATS Keywords
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Hard Skills & Tools
AI/ML engineeringRAG architecturesLLM frameworksVector databasesLLMOpsMLOpsPythonSQLcloud platformsmicroservices architectures
Soft Skills
collaborationinfluencingcommunicationstorytellingleadershipstrategic recommendationsstandardizationreusescalabilitycross-functional teamwork
Certifications
Master's degree or higher