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 3+ years applied experience
5+ years of hands-on experience in the software industry, specializing in Java, Python, AWS (including EKS, S3, Lambda, EMR), and Terraform.
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 exposure to security and infrastructure within cloud environments.
Practical cloud-native development experience specifically in AWS, with a focus on designing and delivering robust solutions.
Demonstrated expertise in software design principles and complete end-to-end, hands-on delivery.
Experience in streaming systems such as Kafka.
Hands-on practical experience delivering system design, application development, testing, and operational stability.
Proficiency in automation and continuous delivery methods.
Preferred qualifications, capabilities, and skills
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security.
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.).
Proficient in all aspects of the Software Development Life Cycle.
Advanced proficiency in one or more programming languages.
In-depth knowledge of the financial services industry and their IT systems.
Proficiency in Data Engineering concepts and related technologies such as AWS EMR and Databricks. Certifications is a plus