Deliver end-to-end cloud-native, microservices-based applications using modern technologies and industry best practices.
Apply domain modeling to build high-quality business products, structuring software for clarity, testability, and evolution.
Write secure, high-quality production code; review and debug code written by others.
Identify opportunities to automate recurring remediation, promptly investigate and resolve issues, and prevent them from recurring to improve operational stability.
Design and build scalable, secure, and reliable systems using modern architectural patterns that avoid single points of failure, enable zero-downtime releases, and optimize data performance.
Keep systems current by continuously adopting relevant technologies, patterns, and leading-edge practices; contribute to Software Engineering communities of practice to share awareness and adoption.
Foster a team culture grounded in diversity, opportunity, inclusion, and respect.
Required qualifications, capabilities, and skills
Formal training or certification on software engineering concepts and 5+ years applied experience.
Proficiency in back-end technologies (e.g., Java, Spring Boot, Node.js) and experience building microservices-based applications; for full-stack roles, proficiency also includes front-end technologies (e.g., HTML, CSS, JavaScript, TypeScript, React, Angular).
Ability to independently solve design and functionality challenges with minimal supervision.
Experience with cloud platforms (e.g., AWS, Azure, GCP), distributed systems, and web technologies, including RESTful APIs, web services, WebSockets, and JSON.
Hands-on experience designing and building scalable applications using SQL and NoSQL databases.
Proficiency across the software development life cycle (SDLC) and experience with Agile methodologies, such as Scrum.
Demonstrated experience leading effective use of enterprise-authorized AI-assisted software development tools within the work environment (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 senior engineers/leads on compliant usage patterns and controls.
Understanding of application resiliency and security principles.
Proficiency in automation and continuous integration and delivery (CI/CD) methods.
Demonstrated proficiency in software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, or mobile).
Preferred qualifications, capabilities, and skills
- Strong soft skills, including presentation, negotiation, mentoring, and stakeholder management.
- Strong problem-solving, analytical, and communication skills.
- Demonstrated experience developing, testing, and maintaining software in Python, including writing clear, reusable code, troubleshooting issues, and using appropriate libraries and frameworks to build reliable solutions.
- Ability to drive broader impact by sharing and contributing best practices.
- Experience in the banking domain.
- AWS certification.
