Lead Software Engineer - Platform AI Acceleration in Glasgow

Lead Software Engineer - Platform AI Acceleration in Glasgow

Glasgow Full-Time 72000 - 88000 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Lead the development of innovative AI systems and reusable APIs to accelerate business delivery.
  • Company: Join JPMorgan Chase, a global leader in financial services with a focus on innovation.
  • Benefits: Enjoy competitive salary, diverse work culture, and opportunities for professional growth.
  • Other info: Be part of a diverse team that values inclusion and fosters career advancement.
  • Why this job: Make a real impact by shaping the future of AI in a dynamic environment.
  • Qualifications: Strong software engineering background with experience in AI/ML and team leadership.

The predicted salary is between 72000 - 88000 £ per year.

As a Lead Software Engineer at JPMorgan Chase within Infrastructure Platforms Applied Artificial Intelligence and Machine Learning (AI/ML), you will join a small, specialist team responsible for creating horizontal capabilities, including reusable APIs, libraries, reference architectures, and practical enablement that accelerates delivery across key products and platforms. This is a hands-on technical specialist role, with the opportunity to create new systems and capabilities that will accelerate our business.

The ideal candidate brings a strong foundation in software engineering and AI/ML, along with proven experience leading the development and production operation of AI-enabled systems in secure, enterprise environments. In this role, you will collaborate closely with engineering teams across our group to develop priority use cases, design and build services, and promote best practices for scalable, resilient, and secure AI adoption. You will also mentor engineers, contribute to firmwide standards and thought leadership, and help ensure the organization stays at the forefront of AI engineering advancements.

Your deep experience of developing and deploying software to production in enterprise environments will be key to enabling our AI strategy, combining practical expertise with AI/ML knowledge to ensure our systems are secure, compliant and performant.

Job responsibilities:

  • Design and develop modular, maintainable AI systems and interfaces aligned to Infrastructure platform standards, optimizing for scalability, resiliency, and long-term operability.
  • Partner closely with Applied AI/ML, Data Science and Cybersecurity engineers to develop secure AI solutions for Infrastructure Platforms and our consumers.
  • Create secure and high-quality production code, and reviews and debugs code written by others.
  • Evaluate AI solution approaches from engineering standpoint to improve overall design quality, code quality, and operational outcomes.
  • Influence peers and project decision makers to adopt leading-edge technologies where they create measurable value.
  • Drives team adoption of enterprise AI-assisted engineering practices to improve code quality, delivery speed, and operational outcomes while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Contribute to the engineering community by advocating firmwide frameworks, tools, and practices for the AI-enabled System Development Life Cycle (SDLC).
  • Foster a team culture of opportunity, inclusion, and respect.

Required qualifications, capabilities, and skills:

  • Significant hands-on system/software development experience, delivering production services in secure, regulated environments.
  • Demonstrated experience leading technical discussions (technical direction, design reviews, quality standards, and operational readiness) across a team or program.
  • Significant experience in at least one modern programming language: Java, Python.
  • Experience using AI coding assistants (GitHub Copilot, Claude Code etc) to complete software engineering tasks.
  • Solid understanding of building AI solutions using an LLM backed architecture.
  • Strong understanding of API design, microservices, and event-driven architectures.
  • Experience building and operating cloud-native services on AWS, including Bedrock.
  • Strong DevOps practices: CI/CD pipelines, containerization (Docker, ECS/EKS), and infrastructure-as-code (e.g., Terraform/CloudFormation).
  • Strong prompt engineering capability, including system prompts, few-shot prompting, tool/function calling, and structured outputs (e.g., JSON schemas).
  • Demonstrated experience driving secure and effective adoption of enterprise-approved AI-assisted engineering tools (coding, review, testing, troubleshooting) and setting team expectations for validating AI outputs for correctness, performance, and security.

Preferred qualifications, capabilities, and skills:

  • Financial Services industry experience.

J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives.

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success.

Full time

Lead Software Engineer - Platform AI Acceleration in Glasgow employer: JP Morgan Chase

Morgan is an exceptional employer, offering a dynamic work culture that prioritises diversity and inclusion while fostering employee growth through comprehensive coaching and development opportunities. As a global leader in financial services, we empower our teams to drive impactful product management and AI enablement, ensuring that every employee can contribute meaningfully to our clients' success in a collaborative environment located at the heart of the financial sector.

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Contact Details:

JP Morgan Chase Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead Software Engineer - Platform AI Acceleration in Glasgow

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at JP Morgan Chase or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

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We think you need these skills to ace Lead Software Engineer - Platform AI Acceleration in Glasgow

Software Development
AI/ML Knowledge
Java
Python
API Design
Microservices
Event-Driven Architectures

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at JP Morgan Chase.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at JP Morgan Chase and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at JP Morgan Chase

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If JP Morgan Chase uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.