Team Lead Engineering - Finance Automation

• You lead a product-focused engineering team that builds and evolves Zeal's core B2B platform capabilities for internal business customers
• In collaboration with your PM you act as the primary partner between Finance and Core Platform Engineering building trusted relationships and translating financial requirements into scalable platform capabilities.
• Drive the automation of reconciliation, accounting workflows, and financial data processing, reducing manual effort and increasing operational reliability.
• Ensure the reliability, integrity, and auditability of finance-critical data across platform services and infrastructure changes.
• Hire, Build and lead a team of 2 engineers: Hire, develop, and grow a high-performing team, fostering an ownership-driven and reliability-focused engineering culture
• Lead technically and strategically, define and drive architectural decisions together with your team
• Code as part of the team: While guiding architecture and strategy, you’ll regularly write code, contribute to features, and help solve complex technical challenges together with your team
• Champion the effective use of AI in your team's engineering workflows (e.g. AI-assisted development and tooling) and explore opportunities to apply AI within the platform's capabilities
• Deliver secure, robust and maintainable technical solutions while focusing on business needs
• Drive collaboration: Work closely with other teams to align APIs, technical interfaces, and architectural consistency
• Own and operate the domain and the team’s microservices.

What you offer us:

• Proven people leadership skills, with an empowering style that enables rather than micromanages
• Ability to translate complex business and financial requirements into scalable technical solutions and platform capabilities.
• Strong and up-to-date hands-on experience working with Kotlin/Spring Boot, SQL (PostgresDB)
• A “You build it, you run it” mindset, with experience in deploying, monitoring, and maintaining microservices on Kubernetes.
• Strong understanding of how to create and evolve Event-driven processing pipelines built on Kafka.
• Strong engineering fundamentals in building secure, scalable, and reliable systems, including security-by-design, resilience patterns, and operating production systems at scale.
• Experience with agentic AI development practices and operating models.