Senior Manager, AI Implementations

BeOne Medicines

Senior Manager for AI implementations in oncology at BeOne. Leading efforts to operationalize AI capabilities across Commercial and Medical teams.

Posted 6/14/2026full-timeRemote • California • 🇺🇸 United StatesSenior💰 $137,400 - $182,400 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudGoogle Cloud PlatformPythonSQLTableau

About the role

Key responsibilities & impact

Lead creation and ongoing governance of a semantic layer on top of the commercial and medical data warehouse.
Partner with data engineering, BI, MDM, and business stakeholders to define how patient, HCP, account, field insight, engagement, journey, patient-level, and medical/commercial data assets should be represented for AI use.
Translate data definitions and business context into reusable metadata, ontologies, knowledge objects, and retrieval patterns that improve AI model grounding.
Support the design of an insight generation engine on top of the data and semantic layers.
Define evaluation criteria for data readiness, retrieval quality, insight accuracy, confidence, freshness, source attribution, and business actionability.
Coordinate across Commercial, Medical, field, compliance, privacy, legal, and technology teams to ensure AI guardrails for free-text inputs and field-collected insights are implemented correctly.
Validate and continuously improve RAG-based chat interfaces across Commercial and Medical teams.
Enhance existing RAG and GenAI models to generate meeting-ready decks, briefs, summaries, talking points, and insight narratives based on unstructured commercial and medical content.
Ensure end-to-end customer and patient journey solutions leverage AI capabilities in the intended manner, grounded in BeOne's data landscape.
Write code and build prototypes, scripts, prompts, evaluation harnesses, APIs, or workflow automations to test and accelerate new AI capabilities.

Requirements

What you’ll need

BS Degree with 7+ years of experience across data products, AI/ML, GenAI implementation, data engineering, BI, or commercial/medical technology in enterprise environments.
3+ years of recent oncology experience focused on patient journeys, patient-level data, customer/HCP engagement, commercial domain, medical domain, and related domain knowledge.
Strong understanding of pharmaceutical/biotech commercial and medical data ecosystems, including patient journey data, field insights, CRM/field activity, medical/commercial knowledge assets, omnichannel engagement, and BI/reporting layers.
Experience building or governing semantic layers, data catalogs, business glossaries, metadata frameworks, ontologies, knowledge graphs, or metrics layers for AI use.
Hands-on experience with GenAI/RAG concepts, including document ingestion, embeddings, vector databases, retrieval strategies, prompt engineering, grounding, evaluation, monitoring, and guardrails.
Coding proficiency in Python and SQL; ability to prototype independently and partner effectively with engineering teams.
Experience with data warehouse, lakehouse, and cloud platforms such as Snowflake, Databricks, AWS, Azure, or GCP; experience with BI tools such as Power BI, Tableau, Qlik, or similar preferred.
Familiarity with LLMOps/MLOps, APIs, workflow automation, data pipelines, and unstructured data processing.
Understanding of data privacy, security, compliance, and responsible AI practices in healthcare/life sciences environments.

Benefits

Comp & perks

Medical
Dental
Vision
401(k)
FSA/HSA
Life Insurance
Paid Time Off
Wellness
Employee Stock Purchase Plan

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

semantic layer governancemetadata frameworksontologiesknowledge graphsGenAIRAG conceptsPythonSQLdata warehousecloud platforms

Soft Skills

collaborationcommunicationproblem-solvingleadershiporganizational skillsdata-driven decision makingadaptabilitycritical thinkingattention to detailstakeholder engagement