R&D Director
EverC
- תל אביב
- משרה קבועה
- משרה מלאה
- Define and drive the technological strategy and roadmap for multiple engineering teams.
- Manage, mentor and develop team leaders, empowering them to build and scale high-performing teams.
- Partner with Product Management and other stakeholders to align priorities with the company’s business objectives.
- Oversee the design and development of large-scale, Gen-AI/ML products and infrastructure.
- Drive engineering best practices across all teams, including coding standards, architecture reviews, testing, and CI/CD.
- Ensure efficient processes and continuous improvement in delivery, quality, and innovation.
- Build organizational capacity by hiring and developing top talent.
- Foster a culture of collaboration, innovation, and accountability.
- Lead and inspire a growing group of engineers through your team leads.
- Ensure smooth execution of cross-team projects and initiatives.
- Guide architectural decisions and influence how data is processed at scale.
- Collaborate closely with the CTO and other executives to set long-term technological direction.
- Track performance and delivery metrics, ensuring alignment with business goals.
- Champion engineering excellence and innovation across the group.
- 3+ years of proven experience as an R&D Director / Senior Engineering Manager, managing multiple teams and team leads.
- 8+ years of hands-on engineering experience with modern technologies (Java, Python, .NET, etc.).
- Strong background in data-centric products, Gen-AI/ML, large-scale distributed systems, and microservices architectures.
- Experience leading large engineering groups in a cloud-based environment (AWS preferred).
- Demonstrated ability to manage complex projects and align them with strategic goals.
- Proven track record as a mentor and leader of leaders.
- Excellent communication and collaboration skills in English.
- BSc in Computer Science or equivalent (MSc – advantage).
- Proficiency in Kubernetes.
- Experience with streaming architectures (Kafka, Kinesis, etc.).
- Hands-on experience with Spark (Scala/PySpark).
- Experience with developing and deploying ML models at scale.
- Experience with Agentic software development.
- Experience with LLMs (serving and fine-tuning).
- Familiarity with CI/CD systems (Github Actions, ArgoCD).
- Experience with infrastructure-as-code tools (Terraform, CloudFormation).