Technical Product Manager

**Responsibilities:**Lead and manage IT projects from initiation to closure, ensuring adherence to timelines and quality standards.
Collaborate with cross-functional teams and stakeholders to achieve project objectives.
Communicate effectively with onshore clients and maintain strong client relationships.
Ensure compliance with IT infrastructure standards and SDLC processes.
Handle multiple tasks and prioritize effectively in a fast-paced environment.
Maintain a strong focus on customer service and teamwork.
Own and drive the product roadmap for healthcare technology products, including data, analytics, and AI capabilities
Define requirements for dashboards, KPIs, analytics, and AI-enabled solutions
Ensure solutions meet healthcare regulatory, compliance, responsible AI, and patient safety requirements.

Mandatory Skills:

Healthcare & Life Sciences

**Mandatory Skills Description:**5+ years in technology product or platform product roles
Demonstrated experience delivering healthcare technology products
Direct exposure to healthcare data, analytics, or AI enabled solutions
Experience operating in regulated environments (HIPAA, PHI, healthcare compliance)
Proven ability to lead complex healthcare initiatives through ambiguity and change

Strong understanding of healthcare operations and workflows, including payer, provider, and care management contexts
Familiarity with healthcare domains such as:
Utilization Management (UM)
Care Management / Case Management
Prior Authorization
Ability to translate clinical and operational workflows into scalable technology solutions
Deep appreciation for regulatory, compliance, and patient safety considerations in product decisions

Outcome driven product mindset grounded in healthcare realities and AI /data first thinking
Ability to identify where data, analytics, and AI improve healthcare outcomes or reduce administrative burden
Roadmap ownership integrating:
Core healthcare capabilities
Data and interoperability foundations
Analytics and AI enablement
Prioritization informed by clinical impact, operational value, feasibility, and risk
Strong problem framing focused on insight generation, automation, and scale

Working understanding of:
Healthcare data domains (member, provider, clinical, authorization, outcomes)
Data flows across payer, provider, and partner systems
Ability to partner with data engineering, analytics, and AI teams to:
Enable reliable healthcare analytics and reporting
Support decision making through insights and AI assisted summarization
Experience defining requirements for:
Operational and clinical dashboards
KPIs tied to quality, efficiency, cost, and experience
AI enabled analytics (summarization, prioritization, decision support)
Awareness of data quality, lineage, interoperability, and adoption challenges in healthcare

Understanding of AI use cases relevant to healthcare:
Clinical and operational summarization
Decision support (human in the loop)
Workflow automation and prioritization
Ability to balance innovation with:
Responsible AI practices
Explainability and auditability
Regulatory and ethical considerations
Experience guiding AI from pilot ? production ? scaled adoption in healthcare settings

Knowledge of modern architectures supporting healthcare data and AI:
APIs, microservices, cloud platforms
Data platforms, interoperability layers, and integration patterns
Ability to evaluate build vs buy vs reuse with healthcare constraints in mind
Comfort navigating legacy systems, technical debt, and complex integrations common in healthcare ecosystems

Agile / SAFe execution with emphasis on progress, readiness, and adoption
Strong dependency and risk management across:
Product teams
Data pipelines
Analytics and AI platforms
Release planning that includes:
Data readiness and validation
Analytics accuracy
AI model monitoring and compliance checks

Trusted partner to business, clinical, and operations leaders
Clear articulation of tradeoffs, risks, and value realization