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.
Develops secure high-quality production code, and reviews and debugs code written by others. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
Leads communities of practice across Software Engineering to drive awareness and use of new and leading-edge technologies. Adds to team culture of diversity, opportunity, inclusion, and respect.
Promptly investigate and resolve issues, ensuring they do not resurface. Continuously update technologies and patterns to keep systems current.
Design and build solutions that avoid single points of failure using scalable architectural patterns.
Design and build scalable, secure, and reliable solutions by leveraging modern architectural patterns that ensure zero-downtime releases and optimize data performance.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years of hands-on experience in software engineering, including system design, application development, testing, and operational support.
Proficiency in back-end technologies (e.g., Java, Springboot, Node.js ) with experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g. JavaScript, Typescript, React, Angular).
Demonstrated ability to independently solve design and functionality challenges with minimal supervision.
Experience working with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs and web services, WebSockets, and JSON.
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
Hands-on experience designing and building scalable applications using SQL and NoSQL databases. Experience with agile development methodologies (e.g., Scrum) and an understanding of the software development life cycle.
Understanding of application resiliency. Proficiency in automation and continuous delivery methods.
Proficient in all aspects of the Software Development Life Cycle. Advanced understanding of agile methodologies such as 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.). Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Preferred qualifications, capabilities, and skills
Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
Strong problem-solving, analytical, and communication skills.
Ability to drive broader impact by sharing and contributing best practices.
Experience in the banking domain.
