
at J.P. Morgan
Bulge Bracket Investment BanksPosted 13 days ago
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**Python Software Engineer III** at JPMorganChase Glasgow. Collaborate in agile teams to design secure, scalable software. Key responsibilities include complex problem-solving, producing architecture artifacts, and driving continuous improvement. Required: Proven software engineering experience, proficiency in Python, familiarity with SDLC, and understanding of agile methodologies. Valuable: Experience with cloud technologies (AWS, Databricks), knowledge of AI/ML trends. Join an innovative culture embracing diversity and inclusion. Leverage enterprise-authorized AI coding assistants to enhance productivity and code quality.
- Compensation
- Not specified GBP
- City
- Not specified
- Country
- United Kingdom
Currency: £ (GBP)
Full Job Description
Location: GLASGOW, LANARKSHIRE, United Kingdom
We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. At JPMorganChase, you'll collaborate with a diverse, agile team to deliver trusted, market-leading technology products in a secure, stable, and scalable way. We value your expertise and encourage you to push the boundaries of what's possible. Join us and be part of a culture that celebrates innovation, inclusion, and continuous learning.
As a Software Engineer III at JPMorganChase within Corporate Technology, you will serve as a seasoned member of an agile team, designing and delivering trusted, market-leading technology products in a secure, stable, and scalable way. You will be responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives.
Job responsibilities
- Execute software solutions across design, development, and technical troubleshooting, thinking beyond routine approaches to build innovative solutions and break down complex technical problems
- Create secure, high-quality production code and maintain algorithms that operate synchronously with appropriate systems
- Produce architecture and design artifacts for complex applications, ensuring design constraints are met throughout software code development
- Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Proactively identify hidden problems and patterns in data, using insights to drive improvements in coding hygiene and system architecture
- Contribute to software engineering communities of practice and participate in events exploring new and emerging technologies
- Foster a team culture of diversity, opportunity, inclusion, and respect through active collaboration and engagement
- 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
- Formal training or certification on software engineering concepts and proficient applied experience
- Hands-on practical experience in system design, application development, testing, and operational stability
- Proficiency in coding in one or more programming languages
- Experience developing, debugging, and maintaining code in a large-scale environment using one or more modern programming languages and database querying languages
- Overall knowledge of the Software Development Life Cycle
- Solid understanding of agile methodologies such as continuous integration/continuous delivery, application resiliency, and security
- Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, Databricks, PySpark, artificial intelligence, machine learning, mobile, etc.)
- 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
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations
Preferred qualifications, capabilities, and skills
- Familiarity with modern front-end technologies and evolving user interface frameworks
- Exposure to cloud technologies including AWS, Databricks, and agentic AI solutions
- Knowledge of industry-wide technology trends and best practices across disciplines such as artificial intelligence, machine learning, and mobile development




