AI ML Lead Field Engagement Products

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.

About The Role

We are seeking an accomplished and forward-thinking AI/ML Lead to drive high-impact AI initiatives for the Field Engagement Hub, powering next‑generation capabilities for U.S. HCP field teams and commercial stakeholders.

This role blends strategic vision, deep technical expertise, and domain awareness in field orchestration, content automation, rep insights, and compliant GenAI applications. You will architect and deploy enterprise-grade AI systems that enhance field productivity, optimize engagement decisions, and scale across omnichannel commercial platforms.

You will also lead R&D, set technical standards, operationalize AI responsibly, and ensure all innovations align with healthcare compliance frameworks.

Key Responsibilities

Strategic AI Leadership for Field Engagement

• Define and evolve the AI strategy for the Field Engagement Hub, aligned with customer engagement, rep efficiency, personalization, and omnichannel activation goals.
• Identify AI opportunities across areas like call planning, HCP segmentation, rep recommendations, next‑best‑action (NBA), content personalization, and compliant conversational intelligence.
• Evaluate emerging AI methods including agent-based systems, fine-tuned domain LLMs, and real‑time inference architectures relevant to field activation.
  
  
  

Technical Architecture & Model Development

• Architect and deploy production-grade AI models supporting field workflows such as:
• Rep copilot and agentic assistance
• Call note summarization and intent extraction
• Rep recommendation engines (NBA/NBR)
• CRM-integrated GenAI functions
• Advanced NLP pipelines for medical/commercial text
• Design scalable RAG pipelines integrated with medical content stores, CRM data, and company knowledge graphs.
• Implement MLOps frameworks ensuring compliant, observable, and auditable AI deployment across GxP‑adjacent environments.
• Optimize model performance for high concurrency and low-latency field usage.
  
  

Cross-Functional Collaboration & Integration

• Work closely with Field Strategy, Commercial Tech, Medical/Compliance, Data Engineering, and Product teams to translate business problems into AI solutions.
• Drive seamless integration with platforms such as Veeva, Salesforce, omnichannel orchestration engines, and enterprise data lakes.
• Establish AI governance and ensure all models meet healthcare regulatory, privacy, and auditing standards.
  
  
  

Team Leadership & Mentorship

• Mentor AI/ML engineers, ensuring strong engineering discipline within the Field Engagement Hub.
• Promote a culture of responsible innovation, rapid prototyping, and measurable business impact.
• Lead technical evaluations for vendor/partner AI platforms used in field engagement.
  
  
  

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related fields.
• 9+ years of AI/ML experience, with 3+ years leading teams or technical initiatives, ideally in commercial/field‑facing environments.
• Strong Python expertise and experience with ML frameworks (TensorFlow, PyTorch, JAX), NLP stacks, and the LangChain ecosystem.
• Hands‑on experience building agentic AI systems, retrieval‑augmented generation (RAG), vector search architectures, and multimodal capabilities.
• Deep experience with MLOps (Docker, Kubernetes, CI/CD, feature stores, model monitoring).
• Expertise with large-scale distributed computing platforms (Spark, Ray) and large dataset processing.
• Experience deploying models on AWS/Azure with GPU/TPU acceleration.
• Strong ability to convert ambiguous business needs—especially from field teams—into technical solutions.
• Demonstrated ability to create compliant and audit-ready AI systems.
  
  
  

Preferred Qualifications

• Experience in healthcare, biopharma, life sciences, or regulated commercial environments.
• Prior work on field engagement, rep enablement, CRM-integrated AI, or commercial analytics platforms.
• Contributions to open-source AI projects or publications in top-tier ML forums.
• Familiarity with generative AI, prompt engineering, graph neural networks, and agent frameworks.
• Ability to scale AI teams and lead high‑impact cross‑functional programs in fast-paced environments.
  
  
  

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

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