Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Software Engineer - Python

J.P. Morgan
Glasgow
8 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer - Machine Learning

Data Scientist / Software Engineer

Senior Data Engineer

Senior Data Scientists/Data Engineers (Palantir, Python, Data Science)

Senior Data Scientists/Data Engineers (Palantir, Python, Data Science)...

Machine Learning Engineer (Databricks)

Exciting opportunity to join the Credit Trading, Markets technology team building out a full end to end strategic trade management capability for the Exotics business within JP Morgan's strategic Athena platform.

As a Lead Python Software Engineer at JPMorgan Chase within the Corporate and Investment Bank Technology team, your role will be pivotal in a rapidly expanding global agile team. You will be involved in all aspects of the Software Development Life Cycle, from analysis and design to development and testing, delivering valuable solutions to our trading and operations stakeholders. Your responsibilities will include collaborating with a high-performing team to deliver critical technology solutions across various technical domains to meet business objectives.

This role will involve developing components for the firm's strategic trading and risk management platform, crafting services in Python with front ends in modern React and Typescript, and implementing trade execution and management functionalities for Fixed Income financial products. Initial tasks will encompass trade processing, including capturing, storing, and feeding trades from exchanges and blotters through to settlement and accounting. A thorough understanding of Agile Delivery Methodologies and Object-Oriented Design is required for this role, along with the ability to excel in a team through outstanding technical contributions, communication, and partnership.

Job responsibilities

  • Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
  • Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
  • Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
  • Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
  • Proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
  • Contributes to software engineering communities of practice and events that explore new and emerging technologies
  • Adds to team culture of diversity, equity, inclusion, and respect

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and applied experience
  • Hands-on practical experience in system design, application development, testing, and operational stability
  • Proficient in coding in one or more languages such as Python
  • Experience with modern web app development using TypeScript and React
  • Experience in developing, debugging, and maintaining code in a large corporate environment with 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 CI/CD, Application Resiliency, and Security
  • Demonstrated knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)

Preferred qualifications, capabilities and skills

  • Familiarity with modern software development
  • Ability to work on large scale systems, navigating unknowns and producing robust solutions to complex issues
  • Knowledge of Fixed Income financial markets products is preferred but not necessary

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.

Machine Learning Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK machine learning hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise shipped ML/LLM features, robust evaluation, observability, safety/governance, cost control and measurable business impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for ML engineers, applied scientists, LLM application engineers, ML platform/MLOps engineers and AI product managers. Who this is for: ML engineers, applied ML/LLM engineers, LLM/retrieval engineers, ML platform/MLOps/SRE, data scientists transitioning to production ML, AI product managers & tech‑lead candidates targeting roles in the UK.