Full-Stack Software Engineer III

Overview

In this role you contribute as a seasoned engineer within Infrastructure Platforms Data Center Services to design and deliver scalable, secure full-stack solutions. You will work on critical technology across frontend and backend domains, shaping architecture and driving continuous improvement in a large-scale financial tech environment. You’ll mentor juniors, share best practices, and leverage AI-assisted tooling to boost code quality and delivery speed. This position offers impact through building trusted, market-leading technology that underpins global markets.

Responsibilities

• Design, develop, and deliver full-stack solutions (React frontend, Node.js/TypeScript and Python backend)
• Produce secure, high-quality production code and reliable algorithms
• Create architecture and design artifacts for complex components
• Analyze large data sets to generate insights and support software improvement
• Identify hidden data patterns to improve coding hygiene and system architecture
• Develop domain expertise relevant to Data Center Services (e.g., UI/UX, backend architecture, testing strategy)
• Contribute to engineering communities through facilitation and content contribution
• Mentor junior engineers and support their growth
• Leverage enterprise-authorized AI coding assist tools to improve quality, speed, and productivity while ensuring secure coding standards
• Utilize SDLC tools and automation to enhance value and efficiency across development workflows

Key requirements

• Formal training or certification in software engineering concepts
• Hands-on experience in system design, app development, testing, and operations stability
• Proficiency in JavaScript/TypeScript (React, Node.js)
• Experience coding in large-scale environments with modern languages and databases
• Solid understanding of agile methodologies, CI/CD, resiliency, and security practices
• Knowledge of software applications and processes in cloud, AI/ML, or mobile domains
• Experience with AI-assisted software development tools and ability to critically evaluate AI outputs
• Understanding of responsible AI use in engineering, including data sensitivity and security

• collaboration
• mentoring
• problem-solving
• React
• Node.js
• TypeScript

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