Associate Director - Technical Capabilities Lead
$129k - $189.2kEli Lilly & Co
At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
Role Summary
This role will own the technical direction, Service operations, stakeholder alignment and innovation for AI-driven detection solutions supporting Adverse Event (AE) and Product Complaint identification. This role bridges deep technical fluency in AI/ML systems (NLP, LLMs, model evaluation, and MLOps) with the ability to navigate complex, cross-functional stakeholder environments — including regular engagement with senior leadership.Key Responsibilities
Capability Technical Leadership- Serve as the primary technical authority for the AI detection solution, guiding model selection, solution architecture and integration design, and automation strategy
- Oversee the operations of the vendor owned AE/PC detection solution, including ensuring service performance meets contracted SLAs and KPIs (e.g., precision, recall, latency, availability)
- Maintain the capability backlog and partner with the business owner to prioritize implementation of new features through the PI planning process
- Be accountable for the delivery of the capability features required to support the global initiatives that use the AE/PC detection service
- Evaluate and oversee the performance (precision, recall, false positive/negative rates), drift, and reliability of AI/ML models used to detect adverse events and product complaints from various data sources (call transcripts, emails, social media, structured/unstructured text)
- Partner with data science and engineering teams to drive model improvements, retraining and fine-tuning cycles, labeled-data and ground-truth curation, and validation processes
- Assess emerging AI capabilities (e.g., LLMs, retrieval-augmented generation, prompt engineering, NLP techniques) for applicability to detection accuracy, scalability, and compliance
- Ensure solution architecture supports auditability, traceability, and regulatory defensibility (e.g., model versioning, data lineage, audit logging) given the safety-critical nature of AE/complaint detection
- Identify opportunities to automate manual triage, classification, and escalation workflows, including confidence-threshold routing and risk-based human-in-the-loop review
- Define technical requirements (APIs, data schemas, and message flows) for automation pipelines and ensure seamless integration with case management and safety databases
- Partner with teams owning solutions consuming the AE/PC detection services to implement the necessary components to build integration pipelines
- Monitor automation performance metrics (e.g., throughput, straight-through processing rate, error rates) and drive continuous improvement
- Manage the contracted team responsible for monitoring AE/PC detection service
- Act as the key liaison between technical teams, business owners, Pharmacovigilance/Quality functions, IT, and Compliance
- Translate complex technical concepts into clear, business-relevant language for non-technical audiences
- Prepare and deliver presentations to senior leadership on solution performance, risks, roadmap, and value delivered
- Manage competing priorities and expectations across multiple stakeholder groups with differing technical fluency and objectives
- Build trust and consensus among stakeholders with varying interests, including Regulatory, Legal, and Quality Assurance
- Ensure the AI solution adheres to relevant global regulatory requirements (e.g., FDA, EMA) for pharmacovigilance and complaint handling systems
- Support audit readiness and documentation
- Collaborate with Quality and Regulatory teams to ensure detection thresholds and escalation logic meet compliance standards
- Bachelor's degree
- 5+ years of experience in AI/ML solution delivery, technical program leadership, or product management
- Strong working knowledge of AI/ML model types (NLP, transformer-based and classification models, LLMs) and their practical application in text/data classification and entity-extraction use cases
- Experience with automation frameworks, workflow orchestration, and MLOps practices (model versioning, CI/CD, monitoring, and drift detection)
- Familiarity with model performance evaluation (precision, recall, false positive/negative rates) in high-stakes/regulated contexts
- Understanding of data pipelines (ETL/ELT), integration patterns (REST APIs, messaging, and batch interfaces), and enterprise system architecture
- Exposure to responsible AI principles, model risk management, or AI governance frameworks is a plus
- Demonstrated ability to manage complex, multi-functional stakeholder relationships
- Excellent verbal and written communication skills, with proven experience presenting to senior leadership/executives
- Ability to translate technical detail into business impact and risk framing
- Strong facilitation and negotiation skills to align diverse stakeholder priorities
- Familiarity with pharmacovigilance, adverse event reporting, or product complaint handling processes
- Understanding of regulatory expectations for safety data systems in the pharmaceutical/life sciences industry
$118.5k - $173.8k
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