Job Description Summary

At GE HealthCare, we are committed to bringing cloud-based solutions for our customers: all aspects of computing services across the cloud and edge – including servers, databases, storage, networking, analytics, software, intelligence are delivered over the Internet. Our Science & Technology organization is harnessing the power of technology to make healthcare more precise, more personalized, and more accessible for everyone. From driving the overall clinical research and patient-centric innovation strategy to delivering new digital and machine learning capabilities - we’re committed to leading digital transformation, improving outcomes for patients and providers, and creating a world where healthcare has no limits.

Job Description

Responsibilities:

As the Senior Director of Technical Program Management, you will drive the success of complex, cross-functional programs in the Digital, Cloud, and AI space, with a focus on delivering cloud-based SaaS solutions and AI-enabled products. You will lead critical initiatives in a highly regulated healthcare environment.

• SaaS Program Management:
  • Lead the end-to-end delivery of SaaS products or cloud-based solutions, from conception to launch, with a focus on operationalizing and scaling the product. Manage milestones, timelines, and cross-functional coordination to meet performance, reliability, and security standards.
  • Oversee SaaS architecture and deployment, including multi-tenant models, microservices, and API management, in cloud environments like AWS, Google Cloud, or Azure.
  • Ensure seamless integration of subscription and billing systems, addressing their impact on revenue, customer retention, and growth.
• Cloud Program Management:
  • Oversee cloud infrastructure supporting SaaS products, focusing on scalability, cost optimization, and service availability.
  • Collaborate with engineering teams to manage large, distributed cloud environments and optimize resource usage.
  • Ensure robust security and compliance in cloud deployments, addressing concerns such as data protection, encryption, identity management, and adherence to standards like GDPR and SOC 2.
  • Drive DevOps processes and maintain efficient CI/CD pipelines to enable rapid and reliable development cycles.
• AI/ML Program Management:
  • Lead the development and integration of AI-enabled features in SaaS products, collaborating with data scientists, machine learning engineers, and software teams to manage the entire AI lifecycle, including data collection, model training, deployment, and iteration.
  • Oversee AI model governance to ensure performance, continual improvement, and alignment with ethical guidelines, mitigating bias and promoting fairness and transparency.
• Program Leadership and Cross-Functional Collaboration:
  • Manage and align multiple cross-functional teams, including engineering, product, data science, marketing, security, and legal, to achieve product and business goals.
  • Communicate complex technical concepts effectively to non-technical stakeholders and senior leadership, ensuring alignment on deliverables and driving accountability.
  • Proactively identify resource needs, manage risks, and implement mitigation plans to adapt strategies and address challenges throughout the program lifecycle.
• AI/Cloud Program Execution and Delivery:
  • End-to-end ownership of delivering AI and cloud-enabled features or products, managing timelines, tracking progress, resolving roadblocks, and driving teams to achieve milestones and deadlines.
  • Deliver scalable, high-performance solutions with minimal downtime, optimizing infrastructure and algorithms for efficiency.
  • Leverage Agile methodologies to manage sprint planning, backlog grooming, and retrospectives, ensuring timelines and technical debt are effectively managed while maintaining quality and iterative development efficiency.
• Metrics, Monitoring, and Performance Optimization:
  • Define and track key performance indicators (KPIs) for SaaS and AI products, including AI model accuracy, latency, scalability, user engagement, uptime, retention, and revenue growth.
  • Implement robust monitoring systems for AI models and cloud-based SaaS products, leading incident response efforts to address outages, performance issues, or bugs.
  • Use data-driven insights and post-launch feedback to continuously refine products and AI components, driving iterative improvements and optimizing performance.

Minimum Qualifications:

• Bachelor’s degree and 6+ or more years of program or project management experience; or an associate degree and minimum 8 years of program or project mana