Revup Payments is a fintech leader in payment orchestration, providing businesses with seamless access to global payment solutions for over four years. Specializing in revenue optimization, we offer card processing and alternative payment methods enhanced by smart routing, fraud prevention, and an intuitive dashboard. Backed by a team of payment and fraud experts, our all-in-one platform is designed to maximize revenue, reduce costs, and improve the payment experience, all through a single API integration. We are seeking an experienced and highly skilled AI Engineering Team Lead (Agents & Developer Productivity) to join our technology team at Revup Payments, a leading global Payment Orchestrator. In this role, you will lead a team of talented engineers while remaining hands-on, driving the design, development, and adoption of AI-powered solutions, particularly AI agents to enhance our software development lifecycle and internal engineering workflows. Your mission will be to embed AI capabilities across the organization, improving developer productivity, code quality, and delivery speed. You will work closely with engineering, product, and platform teams to identify high-impact opportunities where AI can optimize processes such as code generation, testing, incident analysis, and integration of payment methods (including card processing, eWallets, and Alternative Payment Methods). Your technical expertise and leadership will be pivotal in ensuring our platform remains robust, scalable, and innovative, while evolving our engineering practices through the effective use of AI. Key Responsibilities: Lead and mentor a cross-functional engineering team, fostering a culture of collaboration, innovation, and continuous improvement, with a strong focus on AI adoption. Drive the design, implementation, and evolution of AI-powered solutions, particularly AI agents, to enhance software development workflows, developer productivity, and operational efficiency. Act as a hands-on technical leader, actively contributing to system design, code reviews, and the development of AI-driven capabilities integrated into the platform. Identify and prioritize high-impact opportunities to leverage AI across the software development lifecycle, including code generation, testing, debugging, incident analysis, and documentation. Architect and implement scalable and secure systems that combine traditional backend engineering with AI components (e.g., LLM integrations, RAG pipelines, agent-based workflows). Collaborate with product, engineering, and business stakeholders to define AI use cases aligned with company goals and deliver measurable impact. Establish best practices for building, evaluating, and maintaining AI systems in production, including observability, performance, cost control, and reliability. Drive the adoption of AI tools and practices across engineering teams, acting as a mentor and enabler for developers to effectively leverage AI in their daily work. Ensure that AI implementations comply with security and regulatory requirements (e.g., PCI DSS, GDPR, DORA), especially in the context of sensitive financial data. Mitigate technical risks related to both traditional systems and AI components, ensuring platform stability, resilience, and trustworthiness. Contribute directly to the development of high-quality, high-performance software solutions, maintaining a strong hands-on involvement. Diagnose and resolve complex issues in production environments, including those involving AI systems and agent-based workflows. Drive technical decision-making, balancing innovation in AI with long-term scalability, maintainability, and business impact. Drive technical decision-making, balancing long-term scalability with immediate business needs. Foster a culture of innovation, collaboration, and accountability across technical teams. Requirements Bachelor's degree in Computer Science, Software Engineering, or a related field (equivalent experience is valued). Collaborative mindset with the ability to work cross-functionally with Product, DevOps, and Security teams. Over 7 years of professional experience in software engineering, including: 6+ years of experience with Java as the primary programming language. 4+ years leading hybrid engineering teams ( inhouse and outsource). Proven experience in the payment industry, fintech, banking, or financial services, with a solid understanding of high-availability systems, regulatory constraints, and secure architectures. Hands-on experience with AI-assisted development tools and coding agents (e.g., Cursor, kilo.ai , warp.dev, Claude Code, or similar),with the ability to integrate them effectively into real-world engineering workflows. Strong ability to apply AI to real engineering problems, especially in: Developer productivity (code generation, testing, documentation) Automation of engineering workflows Incident analysis and debugging support Deep expertise in software architecture, microservices, and cloud-based solutions in AWS. Using A.I Agents to build Test-Driven Development (TDD) and behavior-driven testing methodologies, ensuring robust, maintainable code. Deep understanding and practical application of Object-Oriented Programming (OOP) principles, including SOLID design, Clean Architecture, and advanced software design patterns. Advanced proficiency in Web/API environments, including: HTTP protocols Designing and consuming RESTful services Creating efficient, secure, and high-performance APIs Proficiency in database design and optimization (e.g., PostgreSQL, MySQL, or NoSQL databases). Familiarity with DevOps practices, CI/CD pipelines, and containerization technologies (e.g., Docker, Kubernetes, Google Cloud Run, AWS Lambda). Excellent problem-solving skills and the ability to make data-driven decisions in a fast-paced environment. Excellent communication skills, with the ability to educate and mentor engineers in AI adoption. High level of ownership and agency, with