AI Technical Project Manager
WebMD•Newark, NJ
•$110,000 - $115,000
About The Position
We are looking for an AI Technical Project Manager to drive the delivery and operational execution of AI-enabled initiatives across Medscape Education. This role sits at the intersection of product, engineering, data science, and operations, ensuring that AI-powered capabilities—spanning clinician learning experiences, supporter-facing offerings, and internal workflows—are delivered efficiently, reliably, and at scale. The role requires strong coordination across multiple stakeholders and systems, with a focus on turning complex AI-driven initiatives into well-structured, executable, and scalable programs.
Requirements
- 5–8+ years of experience in technical project or program management
- 2+ years working on AI/ML or data-intensive products
- Strong understanding of: LLMs, RAG systems, and AI product architectures APIs, data pipelines, and cloud environments MLOps concepts (evaluation, monitoring, lifecycle)
- Experience delivering products in regulated environments (healthcare preferred)
- Strong stakeholder management and coordination skills
- Experience working in cross-functional, matrixed environments
- Strong technical literacy and ability to work with engineering and AI teams
- Structured, execution-focused mindset
- Ability to coordinate complex initiatives across multiple stakeholders
- Risk-aware approach with focus on compliance and quality
- Pragmatic, outcome-driven execution
Nice To Haves
- Experience in medical education, healthcare content, or life sciences
- Familiarity with AI tooling (LLMs, vector databases, prompt engineering)
- Experience managing vendors and SaaS integrations
- Certifications (PMP, Scrum, or equivalent)
Responsibilities
- Own end-to-end delivery of AI initiatives across: AI-enabled learning experiences Supporter-facing products and insights Internal AI-powered workflows
- Define and manage roadmaps, timelines, dependencies, and risks
- Ensure alignment across product, engineering, data science, and business teams
- Drive execution across multiple concurrent initiatives with varying complexity
- Act as the central point of coordination between: Product managers Engineering teams (frontend, backend, AI/ML) Data science and analytics Education business and operations teams
- Facilitate clear communication, decision-making, and prioritization across stakeholders
- Ensure smooth handoffs between product definition, technical implementation, and operational delivery
- Coordinate the delivery of AI/ML solutions that simplify core business processes, improve quality, and increase operational efficiency
- Support the translation of business problems into technical requirements, acceptance criteria, and measurable success metrics
- Coordinate with engineering, data science, and platform teams to ensure: API integrations Observability and monitoring SLAs, incident management, and runbooks
- Coordinate model lifecycle activities in partnership with AI and engineering teams, including: Model validation and bias checks Monitoring and CI/CD for models Retraining cadence and rollback/playbook procedures
- Support production readiness and scalability of AI solutions across environments (POC → pilot → production)
- Maintain clear and structured documentation, including: Architecture decisions (in partnership with engineering) Runbooks and compliance artifacts Post-mortems and learnings
- Support the rollout of AI capabilities into repeatable, scalable operational processes
- Coordinate implementation of: Data pipelines and reporting workflows Program delivery processes Internal tools and automation
- Ensure solutions can be consistently deployed across education programs, not as one-off implementations
- Establish and maintain delivery frameworks, rituals, and tracking mechanisms
- Monitor progress against milestones and proactively manage risks and blockers
- Ensure alignment with: Compliance requirements (e.g., ACCME constraints where applicable) Data governance and privacy standards
- Contribute to improving team efficiency, predictability, and execution quality
- Support the deployment of AI across internal workflows, including: Content production and authoring processes Grant development and program setup Reporting and supporter deliverables
- Help teams adopt new tools and workflows effectively
Benefits
- Health Insurance (medical, dental, and vision coverage)
- Paid Time Off (including vacation, sick leave, and flexible holiday days)
- 401(k) Retirement Plan with employer matching
- Life and Disability Insurance
- Employee Assistance Program (EAP)
- Commuter and/or Transit Benefits (if applicable)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
Number of Employees
501-1,000 employees
