We are seeking a highly motivated Team Lead to manage a small development team responsible for building, maintaining, and integrating in-house applications. The role combines traditional technical leadership with the practical adoption of AI technologies to improve software delivery, code quality, and development productivity. The successful candidate will lead development initiatives, mentor engineers, and drive AI-enabled engineering practices across the department.
1. Team Leadership & Delivery
• Lead and mentor a small team of
software engineers in the development, maintenance, and support of in-house applications.
• Plan, assign, and monitor team activities to ensure timely and high-quality delivery.
• Foster a collaborative, high-performance, and continuous learning culture within the team.
• Provide technical guidance, coaching, and performance feedback to team members.
2. Project & Technical Leadership
• Manage small to medium-sized software projects or serve as Technical Lead on assigned projects.
• Collaborate with business stakeholders, architects, infrastructure teams, and vendors to deliver effective solutions.
• Drive application integration initiatives with internal and external systems.
• Ensure adherence to SDLC processes, architecture principles, security requirements, and software development best practices
3. AI-Driven Software Engineering
• Lead the adoption and application of AI tools, frameworks, and best practices within software development activities.
• Utilize AI technologies to improve coding efficiency, code review quality, testing effectiveness, documentation generation, and overall engineering productivity.
• Establish and govern AI-assisted development standards, ensuring compliance with coding standards, security guidelines, and SDLC requirements.
• Conduct training, knowledge-sharing sessions, and coaching programs to promote effective use of AI development tools across the department.
• Evaluate emerging AI frameworks and tools and recommend practical adoption strategies.
4. Quality & Governance
• Conduct design reviews, code reviews, and technical assessments.
• Ensure software quality, maintainability, scalability, and operational stability.
• Support incident analysis, troubleshooting, root cause investigation, and continuous improvement initiatives.
1. Qualification
• Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a related discipline.
• Relevant professional certifications in software development, cloud technologies, or AI-related domains are advantageous.
2. Work Experience
• Minimum 4 years of hands-on experience in Java software development.
• At least 1-2 years of experience leading a development team or serving as a Technical Lead.
• Proven experience delivering enterprise applications throughout the full Software Development Life Cycle (SDLC).
• Experience in application integration, API development, and enterprise system implementation.
• Practical experience using AI-powered development tools for coding, testing, code review, documentation, or productivity improvement is strongly preferred.
3. Knowledge
• Strong understanding of software architecture, design patterns, clean code principles, and SDLC methodologies.
• Solid knowledge of Java ecosystem technologies such as Spring Boot, RESTful APIs, microservices, and related frameworks.
• Understanding of CI/CD, DevOps practices, version control systems, and automated testing.
• Good understanding of AI-assisted software engineering concepts, AI coding assistants, agent-based development frameworks, and modern AI development practices.
• Knowledge of application security, secure coding practices, and software quality assurance.
• Knowledge of banking and financial services business processes is a strong advantage.
4. Skills
• Strong leadership, team management, and stakeholder communication skills.
• Excellent problem-solving, analytical thinking, and decision-making abilities.
• Ability to lead technical discussions, architecture reviews, and code review activities.
• Ability to coach and develop engineering talent while driving team performance.
• Strong presentation and knowledge-sharing capabilities, particularly in AI adoption and engineering best practices.
• Effective planning, prioritization, and project coordination skills.
• Proficient written and verbal communication skills in English.