Lead Software Engineer – Java, AWS, AI

Overview

In this Lead Software Engineer role within Corporate Technology, you will design and deliver robust, scalable Java applications and cloud-native solutions on AWS. You’ll steer architecture, CI/CD, and AI-assisted engineering practices to improve code quality, speed, and operational outcomes for enterprise platforms. You’ll collaborate with product, architecture, and business stakeholders to translate requirements into technical solutions, mentor junior engineers, and raise the bar on reliability and performance. This is a hands-on leadership role at scale, enabling impact across the firm and its clients.

Responsibilities

• Design and develop Java-based applications for complex enterprise needs
• Lead architecture and implementation of cloud-native AWS solutions with high availability, security, and performance
• Drive adoption and improvement of CI/CD pipelines for faster, reliable software delivery
• Promote and implement enterprise AI-assisted engineering practices (code review/refactoring, test strategy, incident analysis) with standardized validation
• Utilize SDLC tools and automation to enhance value of automation in development workflows
• Collaborate with cross-functional teams to translate requirements into technical solutions
• Conduct thorough code reviews and establish engineering best practices
• Mentor and coach junior engineers to foster learning, ownership, and growth

Key requirements

• Advanced proficiency in Java for large-scale production apps
• Hands-on experience designing/deploying AWS cloud-native solutions (EC2, S3, Lambda, RDS, EKS)
• Proven experience building/managing CI/CD pipelines with industry tools
• Strong understanding of software design patterns, distributed systems, and microservices
• Proven ability to lead technical discussions and influence design decisions across teams
• Hands-on experience with enterprise-authorized AI-assisted development tools and ability to validate AI outputs for correctness, performance, and security
• Understanding of responsible AI use in engineering workflows, data handling, resiliency and security practices, and guidance to peers

• collaboration
• leadership
• mentoring
• Java
• AWS cloud services (EC2, S3, Lambda, RDS, EKS)
• CI/CD pipelines

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