Lead Engineer – Java or Python

Overview

In this Lead Software Engineer role within Finance Technology, you drive secure, scalable, and trusted software solutions as a core technical contributor in an agile environment. You will shape architecture, elevate code quality with AI-assisted practices, and partner with cross-functional teams to deliver impactful financial technology. You’ll lead evaluations, promote modern engineering techniques, and foster an inclusive team culture. This position offers the opportunity to influence how high-volume, mission-critical systems are built and operated at scale.

Responsibilities

• Deliver creative software solutions and troubleshoot complex problems beyond routine approaches
• Develop secure, high-quality production code and review others’ code
• Automate remediation opportunities to improve stability of applications and systems
• Lead architectural design evaluations with vendors and internal teams to ensure applicable and robust solutions
• Lead communities of practice to promote new and leading-edge technologies
• Foster a diverse, inclusive team culture
• Drive adoption of enterprise AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes
• Apply SDLC toolchain knowledge, including AI-assisted development and automation, to increase automation value

Key requirements

• Formal training or certification on software engineering concepts and advanced applied experience
• Strong fundamentals in systems design, data structures, algorithms, and architectural thinking
• Hands-on experience in full-stack or cross-functional development across frontend, backend, data pipelines, or mobile
• Proficiency in Java/Spring Boot, Python/PySpark, GraphQL, or mobile development frameworks
• Experience with cloud platforms (preferably AWS) and relational and distributed data platforms (e.g., Oracle, Databricks)
• Advanced understanding of agile methodologies, CI/CD, resiliency, and secure software practices
• Practical understanding of AI/ML concepts and integrating AI/ML into business apps or data workflows
• Hands-on experience with enterprise AI-assisted development tools and ability to validate AI outputs for correctness, performance, and security
• Understanding of responsible AI use, data sensitivity, secure inputs/outputs, and security/resiliency expectations
• Knowledge of the financial services industry and IT systems

• leadership and mentorship
• cross-functional collaboration
• strong communication
• Java/Spring Boot
• Python/PySpark
• GraphQL

…