Project Manager Technical Project Manager Jobs in Sachse, TX

Job Summary
We are seeking an experienced Technical Project Manager with strong Healthcare Payer domain expertise and experience leading AI, GenAI, and Agentic AI programs. The ideal candidate will drive the successful delivery of intelligent automation and AI-powered solutions that transform member experience, provider operations, claims processing, utilization management, care management, and contact center functions.
The role requires expertise in healthcare payer business processes, AI solution delivery, cloud technologies, data platforms, and cross-functional stakeholder management. The successful candidate will collaborate with business leaders, AI architects, data scientists, engineering teams, compliance stakeholders, and vendor partners to implement scalable, secure, and compliant AI solutions.
Key Responsibilities
• Lead end-to-end delivery of AI and Agentic AI initiatives across healthcare payer operations.
• Define project scope, roadmap, milestones, risks, dependencies, and success metrics.
• Manage multiple concurrent projects using Agile, Scrum, SAFe, or hybrid methodologies.
• Develop project plans, resource forecasts, budget tracking, and executive dashboards.
• Ensure projects are delivered on time, within budget, and meet business objectives.
• Lead implementation of AI Agents, GenAI solutions, Intelligent Virtual Assistants, and workflow automation platforms.
• Coordinate development and deployment of autonomous and semi-autonomous AI agents supporting claims operations, prior authorization, utilization management, care management, provider services, member services, appeals and grievances, and fraud, waste, and abuse detection.
• Drive integration of LLM-powered solutions with enterprise applications and healthcare platforms.
• Define AI governance, monitoring, model evaluation, and operationalization processes.
• Collaborate with Solution Architects, Data Scientists, AI Engineers, and Product Owners.
• Oversee system architecture reviews, AI platform integrations, and deployment planning.
• Ensure scalability, reliability, observability, and security of AI solutions.
• Facilitate technical decision-making and architecture governance discussions.
• Support cloud-native AI deployments across Azure, AWS, or GCP.
• Partner with business stakeholders to identify AI use cases across payer operations.
• Translate healthcare business requirements into technical delivery plans.
• Manage projects involving claims processing, enrollment and membership, benefits administration, provider network management, utilization management, prior authorization, care management, risk adjustment, HEDIS quality programs, and value-based care initiatives.
• Ensure solutions align with CMS, HIPAA, NCQA, and healthcare regulatory requirements.
• Ensure compliance with healthcare privacy, security, and AI governance policies.
• Work with data governance teams to support responsible AI initiatives.
• Mitigate risks related to PHI, PII, AI bias, explainability, and model drift.
• Implement monitoring frameworks for AI effectiveness and regulatory compliance.
• Engage executive leadership, business sponsors, technology teams, and external vendors.
• Facilitate steering committee meetings and leadership reviews.
• Communicate project status, risks, and mitigation strategies.
• Drive organizational change management and user adoption initiatives.
Required Qualifications
• Bachelor's degree in Computer Science, Information Systems, Engineering, Healthcare Informatics, or a related discipline.
• 8+ years of IT Project Management experience.
• 5+ years of Healthcare Payer experience.
• 3+ years of experience managing AI, Machine Learning, GenAI, Conversational AI, or Intelligent Automation programs.
• Strong understanding of SDLC, Agile delivery, and enterprise architecture principles.
• 5+ years of experience managing distributed and cross-functional teams.
Preferred Qualifications
• Healthcare domain exposure.
• Familiarity with FHIR and HL7.
• Experience with AWS, Azure, or GCP.
• Knowledge of model governance and explainability.