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Python Lead Software Engineer

JPMorgan Chase
Glasgow, GBR
Full-time
Lead
Onsite
Discovered 3 days ago
javapython

Full Job Posting

Job responsibilities

  • Interface closely with business stakeholders, quantitative research analysts, and upstream and downstream technology teams across the firm to deliver well-integrated, high-quality solutions
  • Execute creative software solutions across design, development, and technical troubleshooting, thinking beyond conventional approaches to break down complex technical problems
  • Develop secure, high-quality production code while reviewing and debugging code written by others to maintain engineering excellence
  • Identify opportunities to eliminate or automate remediation of recurring issues to improve the overall operational stability of software applications and systems
  • Lead Python service and API design and delivery for risk workflows, ensuring scalability, reliability, and alignment with architectural standards
  • Lead evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented assessment of architectural designs, technical credentials, and applicability within existing systems
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
  • 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
  • Build AI-enhanced user features — including search, summarization, and explanation capabilities — with a human-in-the-loop approach to ensure correctness, security, and compliance
  • Foster a team culture of diversity, opportunity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and advanced applied experience
  • Advanced development experience in Python, Java, or another object-oriented programming language
  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Proficient in all aspects of the Software Development Life Cycle, including automation and continuous delivery methods
  • Advanced understanding of agile methodologies, including continuous integration and delivery, application resiliency, and security practices
  • Demonstrated proficiency in software applications and technical processes within a technical discipline such as cloud, artificial intelligence, or machine learning
  • In-depth knowledge of the financial services industry and its technology systems
  • Practical cloud-native development experience
  • Experience communicating effectively with both business-facing customers and technical teams
  • Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
  • Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices

Preferred qualifications, capabilities, and skills

  • Familiarity with modern front-end technologies and UI development patterns
  • Familiarity with large language model application patterns, including embeddings, retrieval-augmented generation, evaluation frameworks, and guardrails, with experience productizing AI features
  • Experience working in financial services or risk technology environments
  • Exposure to market risk concepts such as Value at Risk, stress testing, or scenario analysis

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