Who you are

• Strong expertise in Java, Spring, gRPC, and backend service development
• Hands-on experience with CI/CD pipelines (Jenkins), Kubernetes, and container orchestration
• Familiarity with cloud platforms (AWS) and migration strategies
• Proven ability to lead design discussions, review code, and enforce engineering standards
• Experience mentoring engineers and managing technical forums
• Knowledge of AI model deployment, automation frameworks, and streaming architectures
• Familiarity with IBM ODM, Kafka, and distributed systems
• Exposure to microservices, Docker, and cloud-native patterns
• Ownership & Accountability: Drives outcomes and sets technical direction
• Collaboration: Works effectively across global teams and stakeholders
• Leadership: Inspires and mentors engineers, promotes technical rigor
• Adaptability: Thrives in fast-paced, evolving environments

What the job involves

• The AI & Decision Engineering Platform powers intelligent, real-time decisioning for Mastercard’s fraud prevention and identity validation solutions
• This program enables streaming analytics, governed decision-making, and outcome management with business agility at global scale
• Our platform leverages business rules engines, AI-driven decisioning, streaming big data clusters, in-memory data grids, APIs, and intuitive UIs to deliver decisions in milliseconds across billions of transactions worldwide
• As a Lead Engineer, you will play a pivotal role in driving technical excellence across multiple projects, mentoring engineers, and shaping the architecture for next generation decisioning capabilities
• You’ll lead design discussions, enforce coding standards, and ensure automation and scalability are at the core of every solution
• Develop backend services using Java, leveraging frameworks like Spring and gRPC for high-performance applications
• Own AI model deployment pipelines, focusing on automation for deployment and validation in production environments
• Drive design discussions and technical forums, propose alternatives, and ensure optimal architecture and coding standards
• Manage Kubernetes clusters, oversee containerized workloads, and support cloud migration (AWS) from on-prem environments
• Mentor and coach engineers, fostering technical excellence and continuous improvement within a team of 8–9 developers and cross-functional stakeholders
• Review code and designs, enforce best practices, and ensure delivery of secure, maintainable, and high-quality solutions
• Collaborate across teams, manage multiple projects, and steer technical training and knowledge-sharing initiatives

Benefits

• Gym membership
• Pension plan
• Share purchase options
• Extra holiday purchase optional
• 25 days holiday (excl. bank holidays)
• Work from home opportunities
• Health insurance