Engineering Manager (AI)

TL;DR

Engineering Manager (AI): Leading and mentoring a team of engineers developing AI-based agents with an accent on architectural design, production deployment, and system monitoring. Focus on managing multi-stream project execution, fostering engineering best practices, and ensuring high-quality delivery across the full lifecycle of AI agent development.

Location: Israel (Hybrid)

Company

hirify.global is the global leader in identity security, protecting human and machine identities with an AI-powered platform for the modern enterprise.

What you will do

• Lead, mentor, and grow a team of developers focused on AI-agent systems.
• Manage team execution including sprint planning, priority setting, and delivery commitments.
• Oversee the end-to-end lifecycle of AI agents from design and implementation to deployment and monitoring.
• Maintain a clear roadmap and capability matrix across multiple agents and integrations.
• Provide hands-on technical leadership, including code reviews and architectural decision-making.
• Communicate project status, risks, and progress to product and cross-functional leadership.

Requirements

• Location: Must be based in Israel
• Strong software engineering background with experience in AI/ML and LLMs.
• Minimum of 3 years of experience in team leadership, mentoring, and managing deliverables.
• Proven track record of shipping complex projects and supporting production systems.
• Experience with cloud environments, modern development practices, and production monitoring.
• BSc in Computer Science or a related field.

Nice to have

• Specific experience in developing or maintaining AI agents or LLM-based systems.
• Ability to balance deep hands-on engineering contributions with people management responsibilities.

Culture & Benefits

• Opportunity to work for a market leader in identity security.
• Hybrid work model fostering both collaboration and flexibility.
• Environment focused on continuous threat prevention and AI innovation.
• Exposure to high-scale, enterprise-grade AI implementation challenges.