R&D Manager (GenAI)

TL;DR

R&D Manager (GenAI): Leading the development of a GenAI-powered SaaS platform for digital investigations with an accent on LLMs, RAG architectures, and agentic workflows. Focus on production stability, team delivery, and scaling high-impact AI systems in a fast-changing environment.

Location: Petah Tikva, Israel

Company

hirify.global is a Nasdaq-listed company providing AI-powered Digital Investigation Platforms to public safety organizations and intelligence agencies worldwide.

What you will do

• Lead day-to-day execution, planning, and prioritization of the development team.
• Collaborate with Product, DevOps, and Customer Success to ensure smooth feature delivery and fixes.
• Own production stability and manage ongoing support processes, including triage and resolution tracking.
• Mentor engineers while maintaining a flat, startup-like culture.
• Drive high engineering standards across code quality, testing, and system reliability.
• Stay hands-on with system architecture, specifically GenAI pipelines, RAG, and agentic flows.

Requirements

• 10+ years of experience in software engineering with a strong backend or full-stack background.
• 3+ years of experience in technical leadership or a hands-on management role.
• Proven experience delivering production SaaS applications.
• Hands-on experience with GenAI/LLM-based systems, including RAG and Agentic workflows.
• Strong system design skills for scalable, distributed systems.
• Experience working in cloud environments, with a preference for GCP.

Nice to have

• Experience with agentic frameworks or multi-step AI workflows.
• Background in fast-scaling startups or innovation teams.
• Experience working with data-intensive systems such as BigQuery.
• Familiarity with DevOps and production environments.
• Experience in high-trust or sensitive data domains.

Culture & Benefits

• Opportunity to work on a real-world GenAI product with significant meaningful impact.
• Collaboration within a small, elite team pushing the boundaries of production AI.
• Direct influence on product direction, system architecture, and engineering culture.
• Operating at the intersection of execution and innovation within a public company.
• Flat, startup-like internal culture.