Lead Software Engineer Java

Job Responsibilities

• Design and develop secure, high-quality production code, and review and debug code written by others
• Provide guidance to software engineers on daily tasks and activities, serving as a technical leader and mentor to the development team
• Serve as an integral member of the development team to create practical solutions in Agile/DevOps environments
• Design and build enterprise-scale, high-volume data processing applications for market surveillance systems, handling large volumes of financial data in batch.
• Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
• Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
• Identify opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Manage stakeholder relationships and communicate clearly with stakeholders, presenting ideas effectively
• Lead communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies
• Drive architectural decisions and technical strategy for data processing and market surveillance solutions
• Champion best practices in coding hygiene, system architecture, and operational excellence

Required Qualifications, Capabilities, and Skills

• Formal training or certification on software engineering concepts and 5+ years of applied experience
• Advanced proficiency in Core Java and Java EE application development and proficiency in automation and continuous delivery methods
• Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• Experience with database programming, understanding, designing and build enterprise-scale and high-volume data processing applications.
• Experience with Oracle SQL optimization and troubleshooting performance
• Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
• Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
• Strong experience with batch processing systems and Autosys for job scheduling and workflow management
• Ability to work under pressure and take ownership of issues with a sense of urgency to solve problems and propose solutions
• Strong analytical and problem-solving skills with ability to multi-task, proactive approach, and attention to detail .Good Communication and Collaboration skills
• Working knowledge of LLMs and AI coding assistants (e.g., Copilot) to accelerate secure coding, test generation, and documentation, with attention to data privacy, prompt hygiene, and traceability.

Preferred Qualifications, Capabilities, and Skills

• Extensive hands-on experience with AWS/Databricks; certifications in AWS, Databricks, and Terraform highly desirable
• Experience in building data pipelines using Apache Spark and financial products knowledge (Futures & Options, FX, Commodities, Equities/Derivatives) and trade lifecycles. Proficiency with AI coding assistants (GitHub Copilot, Windsurfer) and LLM applications in software development
• Experience with market surveillance systems for compliance monitoring and suspicious activity detection and strong stakeholder communication and presentation skills
• Working knowledge of LLMs and AI coding assistants (e.g., Copilot) to accelerate secure coding, test generation, and documentation, with attention to data privacy, prompt hygiene, and traceability.