About this role
Gong is seeking an R&D Manager for AI Agentic Frameworks to lead a specialized team in Tel Aviv developing foundational AI infrastructure. This role suits an experienced backend and AI leader looking to shape autonomous enterprise intelligence platforms within a fast-paced engineering environment.
Role Overview
The R&D Manager will direct a team of engineers to build the core operating system and foundational infrastructure used across Gong engineering. This position involves managing agent sessions, memory management, tool orchestration, durable execution, and multi-tenant isolation. The selected leader will spend roughly half their time on hands-on architecture and code reviews, and the remaining time leading the team, mentoring senior engineers, and collaborating with cross-functional stakeholders in a flexible hybrid work model.
Key Responsibilities
Requirements
Skills and Tools
About the Company
Gong uses AI to transform revenue teams by unifying data, insights, and workflows into a single trusted system. More than 5,000 companies globally use the platform to understand customers, automate sales workflows, and close deals. The organization fosters a culture built on transparency, trust, ambitious goals, and a flexible hybrid work model that supports autonomy and effective work habits.
How to Apply
Interested candidates should visit the official Gong careers page to submit an application.
Skills and tech stack
Questions candidates ask
Where is this job located?
This position is located in Tel Aviv with a flexible hybrid work model.
How many years of experience are required?
Candidates must have 8+ years of backend engineering experience.
What programming languages are required for this role?
High proficiency in Python is required, along with familiarity with Java for backend integrations.
What is the team size this person will lead?
The manager will lead a squad of 3 to 4 senior engineers, totaling a team of about 5 engineers.
How is the time split between technical work and leadership?
The role involves approximately 50% hands-on technical architecture and code reviews, and 50% team leadership, mentorship, and stakeholder alignment.