Lead and grow a team of engineers focused on recommendations (recommendation systems, modeling, controls, policy management, policy deployment, framework mapping).
Drive execution of projects from planning to delivery, ensuring timelines, quality, and stakeholder alignment.
Establish and refine engineering processes around productivity, quality tracking, incident management, and performance recognition.
Hire and develop top technical talent across different seniorities, acting as a bar raiser in interviews.
Provide mentorship, set clear expectations, and manage performance across both high and low performers.
Foster a culture of accountability, collaboration, and continuous improvement.
Collaborate closely with product and design to deliver user-facing features with high impact.
Contribute to long-term application architecture and system design decisions.
Guide the team through production issues and ensure operational excellence.
Requirements
5+ years of engineering management experience, with proven success leading teams in data, ML/AI, or recommendation systems.
Prior experience as a senior IC with deep expertise in backend or data systems.
Strong understanding of AI/ML techniques, especially in recommendation or decision-support systems.
Experience designing and delivering data-driven products that model complex domains (security, compliance, or similar).
Familiarity with cybersecurity frameworks (e.g., NIST, ISO, CIS) and the ability to translate them into technical systems for measurement and progress tracking.
Solid foundation in databases, data modeling, and system design for large-scale, data-intensive applications.
Proficiency in Python and comfort with modern data/ML ecosystems.
Demonstrated ability to hire, mentor, and scale high-performing engineering teams.
Strong communication skills with the ability to clearly articulate complex technical concepts to both technical and non-technical stakeholders.
Experience in B2B SaaS; cybersecurity industry background is a strong plus.