National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Senior Software Engineer Technical Lead

Farringdon
3 months ago
Applications closed

Related Jobs

View all jobs

Senior Software Engineer - Machine Learning

Applied AI ML Lead - Senior Machine Learning Engineer - Commercial and Investment Bank

Software Engineer III - Data Engineer - Python, SQL - Senior Associate

Senior Data/Consulting Engineer

Lead Data Engineer

Senior Machine Learning Engineer

Senior Software Engineer Technical Lead

A leading Bank is hiring a Senior Software Engineer / Technical Lead to drive the development and design of several greenfield retail banking platforms as our client rebuilds its brand to stay ahead of the competition. We are looking for a Senior Engineer with a background in Java, Kafka, and Azure who can provide technical leadership and contribute to the vision and strategy as our client continues through its modernization campaign. Our client is paying a basic salary of £100,000 + 25% bonus + benefits to be based in London with occasional travel to Kent.

Our client is seeking experienced engineers with recent retail / digital banking experience who can design new product roadmaps, focus on architectural challenges, and provide hands-on technical leadership to a team of engineers.

Your responsibilities will include:

Lead the development and implementation of a modern cloud foundation and data platform that is robust, scalable, fully automated, secure, and can support the growth of the business.
Build Scalable Architectures: Leverage modern technologies to design and implement scalable, secure, and high-performing cloud-native solutions.
API Development and Integration: Design and build secure RESTful and GraphQL APIs, ensuring seamless integration with core banking systems (e.g., Mambu) and external services like Open Banking platforms.
Data Engineering and Analytics: Work closely with data teams to define robust data pipelines and scalable cloud-based data platforms using tools like Apache Kafka, Snowflake, or Databricks.
Monitoring and Performance Tuning: Implement advanced monitoring and observability solutions using tools like Prometheus, Grafana, or Datadog to proactively identify and resolve performance bottlenecks.
Code and System Optimisation: Proactively analyse and optimise existing systems for improved performance, scalability, and maintainability. 
Core skill set for this position:

Strong experience building and scaling baking systems (Lending, Payments, or Mortgages) with a focus on security compliance and performance is a must.
Experience leading upon architectural challenges, system scalability, and guidance of engineering teams is a must.
A background in Java, C#, Python, or React development with experience providing hands-on technical leadership is a must.
New Product Ramping (approach to ramping up new products with less-experienced teams, providing clear strategies for facilitating MVP products in market and enabling teams to perform at scale) is a must.
Digita transformation experience, moving from on-premise to modern cloud service using Azure, is a must.Benefits: £100,000 / 25% bonus / 28 days holiday / Holiday Purchase Scheme / Occasional travel / Health Insurance / 13% pension / plus much more.

Senior Software Engineer Technical Lead

National AI Awards 2025

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.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.

The Ultimate Assessment-Centre Survival Guide for Machine Learning Jobs in the UK

Assessment centres for machine learning positions in the UK are designed to reflect the complexity and collaboration required in real-world ML projects. From psychometric assessments and live model-building tasks to group data science challenges and behavioural interviews, recruiters evaluate your statistical understanding, coding skills, communication and teamwork. Whether you specialise in deep learning, reinforcement learning or NLP, this guide offers a step-by-step approach to excel at every stage and secure your next ML role.

Top 10 Mistakes Candidates Make When Applying for Machine-Learning Jobs—And How to Avoid Them

Landing a machine-learning job in the UK is competitive. Learn the 10 biggest mistakes applicants make—plus tested fixes, expert resources and live links that will help you secure your next ML role. Introduction From fintechs in London’s Square Mile to advanced-research hubs in Cambridge, demand for machine-learning talent is exploding. Job boards such as MachineLearningJobs.co.uk list new vacancies daily, and LinkedIn shows more than 10,000 open ML roles across the UK right now. Yet hiring managers still reject most CVs long before interview—often for avoidable errors. Below are the ten most common mistakes we see, each paired with a practical fix and a live resource link so you can dive deeper.