R&D Group Leader

Tel - Aviv Full-time Management

About The Position

Zesty allows engineering teams to effortlessly maximize cloud savings and minimize waste by automating cloud cost optimization. The Zesty AI-driven platform automatically adjusts cloud resources in real-time based on the application needs, optimal cloud usage, and a dramatic reduction in cloud spend. 

Zesty is growing, and we are looking for an experienced R&D Group Leader to join our team. As a Group Manager, you will build and manage best in class teams while working on unique challenges of scale and performance.

Your you will do:

  • Hire, manage and coach teams which includes Team leaders, backend developers, Data scientists and Devops in a fast-paced environment 
  • Defining aggressive improvement goals for the group and the product, while leading the group to achieving these goals
  • Responsibility on designing and developing a highly scalable system through the entire product lifecycle
  • Working hand-in-hand with product managers and the teams to execute features from the requirements to acceptance in the field
  • Work in a multi-cloud environment while using technologies such as Serverless, Redis, Kubernetes, NoSQL, Elasticsearch
  • Continuously discover, evaluate, and implement new technologies


  • 3+ years experience in growing and leading engineering groups, managing several teams and mentoring software team leads
  • Experience leading software development of a complete product end to end from requirements, through architecture, leading the development and testing, delivery and all required processes
  • Expertise Track record in designing and building high performant, fault-tolerant, highly available, and secure distributed systems.
  • Customer and business orientation
  • Vast experience in large-scale backend development in one or more of the following languages: Python, Go, C++, Java, C#
  • Proactive, highly motivated individual with an excellent work ethic and goal-oriented approach
  • Proven technical skills and self-learning ability, capable of thoroughly understanding the functional and technical aspects of a complex system

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