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

Apply Now

Director of Software Engineering - Data Analytics & AI | Glasgow, UK

JPMorgan Chase & Co.
Glasgow
8 months ago
Applications closed

Related Jobs

View all jobs

Test Data Engineer

Senior Data Analyst (Project Controls)

Data Scientist / Software Engineer

Senior Machine Learning Research Scientist

Senior Machine Learning Research Scientist

Senior Machine Learning Research Scientist

Director of Software Engineering - Data Analytics & AI

Job Description

Below, you will find a complete breakdown of everything required of potential candidates, as well as how to apply Good luck.

Drive innovation and solution delivery while leading a technical area and serving as a primary decision maker for your teams.

As a Director of Software Engineering at JPMorganChase specializing in Data Analytics & AI, you will serve as the Glasgow Technology Lead for Liquidity Risk Technology within Corporate Technology's Finance domain. This pivotal role offers the opportunity to drive innovation and solution delivery, impacting teams, technologies, and projects across departments. You will manage 2-3 feature teams, comprising approximately 30 talented individuals, to steer multiple complex projects and initiatives. You will work with petabytes of data and systems that generate billions of rows daily, driving insights and solutions that are critical to our business.

Job Responsibilities

Execute creative software solutions, design, development, and technical troubleshooting, thinking beyond conventional approaches to build innovative solutions.Leverage your expertise to manage and analyze petabytes of data, working with systems that create billions of rows daily to drive impactful insights and solutions.Lead and manage 2-3 feature teams, fostering collaboration and ensuring alignment with strategic goals.Influence team resources, budget, and tactical operations, ensuring the successful execution and implementation of processes and procedures.Oversee coding decisions, control obligations, and success metrics such as cost of ownership, maintainability, and portfolio operations.Deliver technical solutions that can be leveraged across multiple businesses and domains, with a focus on data analytics and AI.Engage with peer leaders and senior stakeholders across business, product, and technology teams to drive strategic initiatives.Lead communities of practice across Software Engineering to promote awareness and adoption of new and leading-edge technologies.Foster a team culture of diversity, equity, inclusion, and respect.

Required Qualifications, Capabilities, and SkillsAdvanced experience leading technologists to solve complex technical challenges.Proven experience developing or leading cross-functional teams of technologists.Experience in hiring, developing, and recognizing talent.Experience in enterprise-scale application design, development, and operational stability.Practical experience with cloud-native technologies and platforms.Hands-on experience with Big Data and distributed computation systems (HDFS, Spark, Apache Flink, Databricks), and proficiency in AI technologies.Proficiency in Java, Python, Spring Boot, and cloud-native foundations.Proficiency with AWS services, including EMR and EKS.

About Us

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.

About the Team

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.#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.