Associate Director - Technical Capabilities Lead
$129,000 - $189,200
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Posted today
SENIORITY
Manager
SALARY
$129,000 - $189,200
About the role
- 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. Automation & Process Ownership
- 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. Stakeholder Management & Communication
- 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. Governance & Compliance
- 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. Preferences Technical Expertise
- 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 Communication & Stakeholder Management
- 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 Domain Knowledge (preferred, not required)
- Familiarity with pharmacovigilance, adverse event reporting, or product complaint handling processes
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