Engineering Manager, AI Data Platform

This is a fully remote position, open to applicants in New York.

📋 Description

• Recruit and oversee a team of data engineers ranging from entry-level to mid-level professionals.

• Develop and implement team processes, foster an engineering culture, and establish development practices.

• Mentor and advance engineers at various levels of experience.

• Assume complete technical and operational responsibility for the AI Data Platform.

• Ingest, anonymize, transform, and deliver clinical imaging data, including DICOM files and reports.

• Guarantee that the platform remains reliable, scalable, and secure.

• Define the technical strategy and execute the platform's roadmap.

• Focus on scalability enhancements, new functionalities, and mitigating technical debt in line with business OKRs.

• Introduce data quality frameworks, validation processes, and governance measures.

• Ensure adherence to HIPAA and other relevant regulations.

• Act as the main liaison for AI, Product, Clinical, and Regulatory teams.

• Convert stakeholder requirements into a prioritized roadmap and ensure dependable delivery.

• Report directly to the Head of Engineering and collaborate with the Chief AI Officer, Product leaders, Clinical team, and engineers throughout the organization.

⛳️ Requirements

• Driven by a mission and passionate about developing foundational technology to enhance healthcare.

• Over 8 years of experience in software or data engineering.

• A minimum of 2 years in an engineering management position.

• Proven experience in building engineering teams or scaling teams during significant growth phases.

• Strong technical background in data engineering.

• Proficient in reviewing system designs, making architectural decisions, and contributing code in Python and SQL as necessary.

• Experience with cloud-native data platforms and contemporary data infrastructure, including data lakes, data warehouses, ETL/ELT pipelines, and workflow orchestration tools like Airflow, Prefect, or Dagster.

• Demonstrated capability to manage cross-functional stakeholders and translate business requirements into engineering priorities.

• Experience in a fast-paced, high-growth environment where priorities may shift and ambiguity is common.

• Bachelor’s degree in Computer Science or a related discipline, or equivalent practical experience.

• Background in healthcare, healthtech, or another regulated industry is preferred.

• Familiarity with MLOps or building infrastructure that supports machine learning workflows is preferred.

• Experience with multi-cloud environments and cloud cost optimization is preferred.

🏝️ Benefits

• Equity

• Benefits

• Remote work