Engineering Manager, Safeguards Data Infrastructure (AI)

TL;DR

Engineering Manager, Safeguards Data Infrastructure (AI): Leading the development of the offline data stack for AI safeguards with an accent on data portability, privacy-preserving interfaces, and regulatory compliance. Focus on scaling infrastructure across cloud environments, ensuring HIPAA compliance, and designing zero data retention architectures.

Location: Hybrid in New York City, NY (minimum 25% office attendance required)

Salary: $405,000 – $485,000 USD

Company

hirify.global is a public benefit corporation dedicated to creating reliable, interpretable, and steerable AI systems that are safe and beneficial for society.

What you will do

• Lead and grow a team of engineers delivering data infrastructure and tooling that powers AI safeguards.
• Own the strategy and execution for porting the safeguards offline data stack across new cloud and deployment environments.
• Build and maintain privacy-safe data APIs and interfaces to enable ML and training workflows while respecting data constraints.
• Manage privacy incident response and partner with compliance teams on regulatory requirements such as HIPAA and EU privacy regulations.
• Collaborate with enterprise customers and product teams on zero data retention offerings.
• Coach and mentor direct reports and partner with recruiting to attract and retain top engineering talent.

Requirements

• 3+ years of front-line engineering management experience.
• Prior hands-on software engineering experience as an individual contributor.
• Experience working cross-functionally across infrastructure, product, and compliance or security teams.
• Ability to drive technical decisions in ambiguous, fast-moving environments with competing priorities.
• Must be based in or able to work from the New York City office at least 25% of the time.

Nice to have

• Track record of leading teams building and operating data infrastructure at scale.
• Experience with multi-cloud or multi-region data portability in regulated environments.
• Experience building privacy-preserving data pipelines or interfaces for ML workloads.
• Knowledge of enterprise data contracts or zero data retention architectures.
• Strong understanding of data privacy principles, PII handling, and compliance frameworks.

Culture & Benefits

• Collaborative "big science" research environment focusing on high-impact AI safety.
• Competitive compensation with optional equity donation matching.
• Generous vacation and parental leave policies.
• Flexible working hours and high-quality office spaces.
• Visa sponsorship available for qualified candidates.