Director, Product Engineering & AI

Capital Health (US)•Hopewell, NJ

1d•Onsite

About The Position

The Director, Product Engineering & AI is a strategic and operational technology leader responsible for advancing Capital Health’s internal product engineering, AI-enabled workflow transformation, and enterprise automation initiatives. This role leads the design, development, integration, and operationalization of internally developed digital solutions that improve clinical, operational, financial, and patient experience outcomes across the organization. The Director is responsible for establishing a modern product engineering operating model that combines software engineering, AI technologies, workflow transformation, and enterprise integration principles to deliver scalable and sustainable solutions aligned with organizational priorities. Partners closely with operational, clinical, analytics, infrastructure, and security leaders to identify high-value opportunities for automation, operational intelligence, and AI-enabled transformation. Balances strategic leadership with practical execution and is expected to build a high-performing engineering culture focused on agility, accountability, scalability, security, and measurable business value.

Requirements

Bachelor’s degree in Computer Science, Data Science, Engineering, or related field required.
Eight years of progressive experience in software engineering, enterprise applications, digital transformation, or healthcare technology leadership.
Five years leadership experience managing technical engineering, application development, or digital product teams.
Experience leading cross-functional technology initiatives involving enterprise integrations, workflow transformation, or AI-enabled solutions.
Strong understanding of modern software engineering principles, APIs, cloud-native architectures, and enterprise integration strategies.
Understanding of AI technologies including large language models, workflow automation, AI-assisted applications, and orchestration frameworks.
Strong operational and workflow transformation mindset with the ability to connect technology capabilities to measurable organizational outcomes.
Ability to lead technical teams while balancing strategic priorities, operational realities, and execution discipline.
Strong understanding of agile delivery concepts, product development, lifecycle management, and engineering governance principles.
Ability to collaborate effectively across clinical, operational, financial, and technical leadership teams.
Strong communication and executive presentation skills.
Understanding of cybersecurity, secure development principles, identity management, and enterprise governance expectations.

Nice To Haves

Master’s degree in Healthcare Informatics, Data Analytics, AI, or Business Administration preferred.
Training or certifications in cloud platforms, AI technologies, product management, agile methodologies, healthcare informatics, or enterprise architecture preferred.

Responsibilities

Leads the enterprise Product Engineering & AI function across Capital Health.
Develops and operationalizes a scalable internal product engineering model aligned with organizational transformation priorities.
Leads teams responsible for AI-enabled applications, workflow automation, enterprise integrations, operational tooling, and internally developed digital platforms.
Partners with operational and clinical leaders to identify high-value workflow transformation opportunities.
Establishes engineering standards, architectural governance, development practices, and secure software lifecycle processes.
Oversees the prioritization, planning, execution, and operationalization of internally developed products and automation initiatives.
Collaborates closely with Infrastructure, Security, Analytics, Clinical Applications, Revenue Cycle, and Enterprise Operations teams.
Drives responsible adoption of AI technologies while ensuring alignment with organizational governance, compliance, privacy, and cybersecurity expectations.
Establishes measurable success metrics and value realization processes for transformation initiatives.
Mentors and develops engineering and technical staff capabilities.