Senior Manager - Data Engineering & AI

Job Summary:

The Senior Manager, AI & Data Engineering leads a team of data engineers and AI specialists to deliver scalable, secure, and compliant data solutions that power healthcare SaaS applications.

This role drives innovation in AI/ML, data architecture, and analytics to support strategic business outcomes. The manager collaborates cross-functionally to integrate intelligent data capabilities into products and ensures alignment with healthcare compliance standards.

Key Responsibilities:

1. AI/ML Engineering & Innovation:

- Proven experience designing and implementing AI/ML models for healthcare applications.

- Ability to drive innovation in predictive analytics, clinical decision support, and intelligent automation.

2. Data Architecture & Engineering:

- Expertise in building robust data pipelines, data lakes, and scalable cloud-native infrastructure.

- Strong understanding of data governance, quality, and performance optimization.

3. Healthcare Compliance & Security:

- Deep knowledge of HIPAA, HL7, FHIR, and other healthcare data standards.

- Ensures secure handling of sensitive health data and compliance with regulatory frameworks.

4. Leadership & Team Development:

- Leads and mentors a team of engineers and AI specialists.

- Promotes a culture of technical excellence, collaboration, and continuous improvement.

5. Cross-Functional Collaboration & Strategic Execution:

- Partners with product, engineering, and clinical teams to align data solutions with business goals.

- Manages multiple priorities in a fast-paced environment and communicates effectively across teams.

Required Qualifications:

Education & Experience:

- Bachelors or Masters degree in Computer Science, Data Science, or related field.

- 15+ years of experience in software/data engineering, including 5+ years in leadership roles managing cross-functional engineering teams.

- Minimum 5 years of hands-on experience in AI/ML and cloud-based data platform development.

Other Preferred Knowledge, Skills, Abilities or Certifications:

- Certifications in AI/ML or cloud platforms (Azure, AWS, GCP).

- Familiarity with healthcare interoperability standards (FHIR, HL7).

- Experience integrating AI into SaaS platforms.