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BeOne Medicines

Associate Director, AI Enablement – Commercial & Medical Affairs

BeOne Medicines

Associate Director, AI Enablement at BeOne leading enterprise AI platforms and capabilities. Focusing on engineering and operationalizing AI systems for commercial and medical applications.

Posted 5/28/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $144,300 - $194,300 per yearWebsite

Tech Stack

Tools & technologies
AWSAzureCloudDistributed 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