Software Engineer II - Cloud Technology
JPMorgan Chase · United Kingdom · 19d ago
Mid levelOn-siteSoftware Engineering
Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.
You’re ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you.
As a Software Engineer II at JPMorganChase within the Corporate Sector, Infrastructure Platforms team you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
As a Software Engineer II at JPMorganChase within the Corporate Sector, Infrastructure Platforms team you are part of an agile team that works to enhance, design, and deliver the software components of the firm’s state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job responsibilities
- Securely enable and manage services for the Azure and Google Cloud platforms at JPMorganChase.
- Executes standard software solution, design, development, and technical troubleshooting.
- Writes secure and high-quality code using the syntax of at least one programming language with limited guidance.
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications.
- Applies technical troubleshooting to breakdown solutions and solve technical problems of basic complexity.
- Gathers, analyzes, and draws conclusions from large, diverse data sets to identify problems and contribute to decision-making in service of secure, stable application development.
- Learns and applies system processes, methodologies, and skills for the development of secure, stable code and systems.
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards.
- 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.
Required qualifications, capabilities, and skills:
- Practical cloud native experience including knowledge of Terraform with experience in Azure and Google Cloud
- Formal training or certification on software engineering concepts and 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
- Demonstrated ability to code in one or more languages (Python)
- Experience across the whole Software Development Life Cycle
- Exposure to agile methodologies such as CI/CD, Application Resiliency, and Security
- Emerging knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations.
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated outputs.
Preferred qualifications, capabilities, and skills:
- Knowledge of security best practices in cloud environments
- Desire to learn and continuously grow
- Experience with writing and managing Azure Policy
- Experience with writing and managing GCP Organization Policy
- Cloud certifications (e.g. GCP, Azure, Hashicorp)