Lead Software Engineer - Multiple Teams

• Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
• Develops secure and high-quality production code, and reviews and debugs code written by others
• 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.
• Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
• Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture

Required qualifications, capabilities, and skills

• Formal training or certification on software engineering concepts and 8+ years’ applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Proficient hands-on experience in Java, Go-Lang programming languages using micro-services architecture
• Strong database fundamentals across both SQL and NoSQL, including data modeling and design patterns, indexing strategies, query optimization, and transaction management
• Hands-on experience deploying and operating workloads in private Kubernetes environments and within the AWS Kubernetes ecosystem (e.g., EKS), including Deployments, Services, Ingress, configuration and secrets management, and autoscaling
• 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
• Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
• In-depth knowledge of the financial services industry and their IT systems

Preferred qualifications, capabilities, and skills

• Messaging/streaming systems (Kafka/SQS/SNS/RabbitMQ) and event-driven architectures.
• Experience with service mesh / advanced traffic management (e.g., Istio/Linkerd) and API gateways
• Infrastructure-as-Code exposure (Terraform/CloudFormation) and environment automation