Lead Developer

Overview

As Lead Java Engineer with AI proficiency, you will shape the FTSE Russell Index Platform through high-performance, data-intensive engineering. You will build and integrate AI-driven capabilities, lead end-to-end delivery with cross-functional teams, and ensure scalable, production-ready systems. The role blends hands-on coding with architectural leadership in a global, collaboration-driven environment. Your work will enable precise index computations and trusted client-facing products, driving innovation in financial markets.

Pay / Benefits

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives
• learning tools
• equal opportunities

Responsibilities

• Design, develop and maintain complex Java and Python applications using modern practices
• Embed AI-powered features into mission-critical systems
• Architect and enhance services for large-scale, performance-sensitive index computations
• Collaborate with Product Managers, UX and global engineering teams to deliver high-quality products
• Lead projects end-to-end across requirements, design, development, testing, deployment and operations
• Build and maintain automated test suites for performance, scalability and security
• Diagnose production issues, provide root-cause analysis and Level 3 support
• Conduct peer reviews, provide technical leadership and mentor junior engineers

Key requirements

• 12+ years of hands-on backend software engineering experience
• Support AI adoption and develop intelligent solutions using LLMs, LangChain/LangGraph, and agentic AI frameworks
• Establish best practices for safe, scalable, traceable AI deployments
• Strong algorithms, data structures and ability to translate business problems into scalable solutions
• Proficiency in Core Java and Python
• Experience building distributed, data-intensive systems and microservices with REST APIs
• RDBMS experience (Oracle/SQL Server/Postgres)
• CI/CD tools (Jenkins/GitLab) and DevOps automation
• Docker, Kubernetes and JVM performance optimization
• Prior exposure to Level 3 production support
• Familiarity with Spring Boot, Redis, Kafka and in-memory caching
• Experience with BDD frameworks (Cucumber, JBehave, Karate) and Agile teams

• leadership and mentorship
• problem solving
• collaboration across global teams
• Core Java
• Python
• distributed systems

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