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Software Engineer III - Python, Databricks & AI

JPMorgan Chase
Glasgow, GBR
Full-time
Mid
Onsite
Discovered 1 weeks ago
awsdatabrickspython

Full Job Posting

Job responsibilities

  • Execute software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems
  • Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by 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 and use these insights to drive improvements to coding hygiene and system architecture
  • Contribute to software engineering communities of practice and events that explore new and emerging technologies
  • Leverage 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
  • Apply 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
  • Strong hands-on data engineering experience with Databricks and AWS
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Proficiency in coding in Python
  • Solid understanding of agile methodologies such as CI/CD, application resiliency, and security
  • Overall knowledge of the Software Development Life Cycle
  • Curiosity and foundational understanding of Generative AI, large language models, and AI/ML solutions
  • 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

  • Experience working within large-scale financial platforms supporting reporting, reconciliation, or controllership functions
  • Familiarity with enterprise-scale data pipelines and event-driven architectures
  • Exposure to audit-ready reporting frameworks or financial data governance practices
  • Experience contributing to or leading engineering communities of practice

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