Verint
Software Engineering Manager
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Role Purpose
As a Manager Software Engineering, the individual is entrusted with the strategic oversight of multiple software engineering team leaders and their teams. This role demands a visionary approach to align the teams’ efforts with the overarching goals of the R&D department. The Manager is responsible for nurturing an environment that promotes innovation, efficiency, and quality. They are tasked with optimizing team performance through effective resource management, advocating for best practices in software development, and ensuring that the engineering output not only meets but exceeds customer engagement standards.
Some of your responsibilities:
- Provide strategic direction for multiple software engineering teams.
- Oversee budget allocation and financial planning for software development activities.
- Participate in P1 production incident calls and major customer escalations as needed, providing architecture-level technical guidance to support incident triage, root cause analysis, mitigation planning, and long-term corrective actions.
- Lead the design, development, testing, publishing, and support of different cloud-based products and solutions and provides subject matter expertise for customer implementation and cloud platform support.
- Retention and professional growth of the engineering team leads and their teams.
- Overall performance of the teams in terms of project completion and quality.
- Efficiency in the use of resources across projects.
- Growth and advancement of Team Leaders.
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Essential:
- Experience of full stack development
- Experience of Java and/or NodeJS
- Familiarity with JavaScript UI library such as React, Angular or Vue
- Strong experience with SQL and relational data modeling for scalable enterprise applications.
- Experience with containerized runtime environments: Docker, Kubernetes
- Experience with one of the Cloud hosting services: AWS, Azure, or GCP
- Experience with REST API and microservice applications
- Experience integrating AI/ML, generative AI, or intelligence services into enterprise software products.
- Familiarity with LLM-based application patterns, including prompt orchestration, retrieval-augmented generation, semantic search, and AI-assisted workflows.
- Understanding of responsible AI principles, including data privacy, security, explainability, bias mitigation, and safe handling of customer data.
- Proven commercial experience working within software engineering along with team lead experience.
- Ability to work within a geographically distributed development team spread between multiple time zones and cultures.
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