Java AI Engineer III: Scalable Secure Systems

JPMorgan Chase & Co.

Scotland

On-site

GBP 70,000 - 100,000

Full time

4 days ago

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Job summary

JPMorgan Chase & Co. is seeking a Software Engineer III to join an agile team building trusted, market-leading technology for global operations.

You will implement solutions across multiple domains, improve performance, security, and resilience of critical systems, and contribute to scalable, production-grade software. You will work with Java technologies (Spring/Spring Boot), REST services, and enterprise AI-assisted development tools, while collaborating with peers to deliver robust, compliant

Qualifications

Formal training or certification in software engineering concepts.
Hands-on experience using enterprise-authorized AI-assisted software development tools with ability to critically evaluate AI outputs.
Understanding of responsible AI use in engineering workflows, secure handling of data, resiliency and security practices.
Proficiency in Java technologies and frameworks such as Spring and Spring Boot, and REST-based services.
Proficiency in Unix/Linux environments and navigating systems.
Experience in system design, application development, testing, and operational stability.
Experience coding in modern languages and querying databases.
Understanding of agile methodologies, CI/CD, application resiliency, and security practices.
Knowledge of cloud, AI, machine learning, or mobile technologies.

Responsibilities

Execute software solutions across design, development, and technical troubleshooting to break down complex problems and deliver innovative outcomes
Create secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems
Produce architecture and design artifacts for complex applications, ensuring design constraints are met throughout the SDLC
Gather, analyze, synthesize, and develop visualizations and reporting from large datasets to improve software applications and systems
Identify hidden problems and patterns in data to improve coding hygiene and system architecture
Leverage enterprise AI coding assist tools to improve code quality, delivery speed, and productivity while validating outputs through peer review and secure coding standards
Apply knowledge of the SDLC toolchain, including enterprise AI-assisted development and automation capabilities, to improve automation
Contribute to a team culture of diversity, opportunity, inclusion, and respect