Job Description:
Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness.
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.
Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience
Hands-on practical experience in system design, application development, testing, and operational stability
Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security.
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices.
Overall knowledge of the Software Development Life Cycle
Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
Experience using AI coding assistants (GitHub Copilot, Cursor, Claude, etc.) to accelerate development cycles, and ability to coach teams to adopt these tools as standard practice.
MUST HAVE skills: -------------> 5 years Core Java
Spring Boot
Microservices
Kafka
Cloud - AWS
Preferred qualifications, capabilities, and skills
Experience creating scalable microservices using Java, Spring Boot, Kafka for financial services; utilizing CI/CD toolsets, including GIT, Maven, Jenkins, SonarQube, Junit, and Mockito to develop high-quality software
Experience in AWS services (ECS, VPC, S3, IAM, Lambda, Aurora Postgres, Route53, ELB, API Gateway), Terraform for Infrastructure as Code (IaC), and practical cloud-native experience.
