Applied AI Health Data System Engineer-Senior Manager

About the role

PwC’s Applied AI Health System Engineering team seeks a Senior Manager to lead the development of AI, GenAI, and ML solutions tailored to the complex needs of health system and health plans. This role involves overseeing the development of healthcare AI and GenAI solutions, leading large healthcare data science engagements, and managing global healthcare data science teams.

Responsibilities

• Oversee the development of healthcare AI and GenAI solutions, including clinical use case design, analytical modeling, prompt engineering, and RAG pipeline development
• Lead large healthcare data science engagements, innovating delivery processes and driving continuous improvement across use case development lifecycles
• Maintain operational excellence while engaging health system clinical, financial, and operational leaders at a senior level to align AI initiatives with organizational priorities
• Guide teams in processing clinical notes, claims data, ADT feeds, and other structured and unstructured healthcare data sources for use in AI and LLM-powered solutions
• Manage daily operations of a global healthcare data science team, overseeing model development, MLOps practices, and model governance across client engagements
• Contribute to the creation of healthcare AI proof of concepts, pilots, and production use cases spanning clinical decision support, revenue cycle, population health, research (including images and genomics) and operational optimization
• Foster a collaborative environment across clinical, technical, and operational team members to solve complex health system data science challenges
• Maintain excellence in client service and satisfaction, helping health system clients realize tangible value from AI and ML investments

Requirements

• Bachelor's Degree
• 12 years of experience, with meaningful exposure to healthcare data science, health IT, or AI solution development for health system clients
• At least 6-7 years of experience at a health system

Preferred Knowledge/Skills

• Demonstrates in-depth level abilities and/or a proven record of success managing the identification and addressing of health system needs
• Domain expertise in the healthcare value chain including but not limited to Claims, Pharmacy, Finance, Clinical Domains
• Managing development teams in building healthcare AI and GenAI solutions, including analytical modeling, prompt engineering, Python-based development, testing, communication of results to clinical and operational stakeholders, front-end and back-end integration, and iterative use case development with health system clients
• Collaborating with health system client teams — including clinical informatics, population health, and IT leaders — to understand their business and clinical problems and select the appropriate models, LLMs, and approaches for AI/GenAI use cases
• Designing and solutioning AI/GenAI architectures for health system clients, including RAG-based clinical knowledge retrieval systems, agentic AI workflows for care management and revenue cycle automation, and custom LLM application builds with appropriate PHI safeguards
• Managing teams to process healthcare unstructured and structured data — including clinical notes, discharge summaries, claims records, EHR data, and ADT feeds — for use as LLM context, including embedding of large clinical text corpora, generative SQL query development, and building connectors to EHR back-end databases
• Managing daily operations of a global healthcare data science team on client engagements, reviewing developed models, providing feedback, and assisting in analysis of clinical and operational outcomes
• Directing data engineers and other data scientists to deliver efficient, HIPAA-compliant solutions that meet health system client requirements for clinical, financial, and operational AI use cases
• Leading and contributing to development of proof of concepts, pilots, and production use cases for health system clients — spanning clinical decision support, prior authorization automation, patient risk scoring, workforce optimization, and throughput modeling — while working in cross-functional teams
• Facilitating and conducting executive-level presentations to health system leadership showcasing GenAI and ML solution capabilities, use case development progress, model performance, and recommended next steps
• Structuring, writing, communicating, and facilitating client presentations that translate complex AI and ML concepts into clear clinical and business value narratives for health system audiences
• Managing associates and senior associates through coaching, providing feedback, and guiding work performance, with an emphasis on developing healthcare domain knowledge alongside technical AI and ML capabilities
• Experience with Azure (including Azure OpenAI Service, Azure Machine Learning, and Azure Health Data Services), AWS (SageMaker, Bedrock), and/or Google Cloud (Vertex AI) platforms, with an understanding of PHI-compliant deployment patterns and HIPAA-aligned cloud configurations
• Experience with data warehouse technology including Snowflake or Databricks
• Experience working with Anthropic – Claude and Claude code to accelerate development and build applications
• Experience with Git version control, unit/integration/end-to-end testing, CI/CD, and MLOps practices including model monitoring, performance drift detection, and model governance frameworks appropriate for regulated healthcare environments

Benefits

The salary range for this position is: $124,000 - $280,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus.

PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link: https://pwc.to/benefits-at-a-glance

For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, where ap