What we’re all about.
Do you ever have the urge to do things better than the last time? We do. And it’s this urge that drives us every day. Our environment of discovery and innovation means we’re able to create deep and valuable relationships with our clients to create real change for them and their industries. It’s what got us here – and it’s what will make our future. At Quantexa, you’ll experience autonomy and support in equal measures allowing you to form a career that matches your ambitions. 41% of our colleagues come from an ethnic or religious minority background. We speak over 20 languages across our 47 nationalities, creating a sense of belonging for all.
Opportunity
As a Software Engineer at Quantexa, you’ll play a key role in shaping one of the most critical components of our Decision Intelligence platform: Decision Systems.
The Decision Systems team is responsible for turning complex, interconnected data into actionable insights — helping global organizations detect patterns, uncover risks, and make smarter decisions. You’ll work across the software stack, from enhancing our scoring capabilities to uncover financial crime, to building tools that make detection logic easier and more powerful for our users. Your work will directly influence how clients identify suspicious activity and protect their businesses.
This isn’t just about coding, stakeholder management will be a growing focus of this role. You’ll have the autonomy to take features from concept to release, collaborating closely with product teams and delivery experts to design solutions that make a real impact. You’ll be part of a talented, supportive team that values innovation, knowledge sharing, and continuous improvement, working closely with and learning from our senior and lead engineers.
The role is focused on software development using the latest in agentic AI tooling, with an emphasis on translating requirements into well-engineered, working features. Typical tasks in the team are:
Building new tooling to allow users to configure detection logic more easily and effectively
Enhancing the platform so that existing Scores can be applied across a wider range of scenarios
Improving the performance of the system so even the largest datasets can be analysed efficiently
There are 3 different sub-teams within Decision Systems, each focusing on different areas across the scoring capability within Quantexa. Specifics of the remit and differences between these teams can be shared upon request.
We have a great team culture, with regular socials and a strong presence in Quantexa’s London office, whilst maintaining a flexible working policy allowing for regular home working. Come and be a part of the next stage of the growth of our team and Quantexa as a whole!
Requirements
What do I need to have?
Take pride in designing, building and delivering high quality well engineered solutions to complex problems
Take a big picture approach to solving problems, taking care to ensure that the solution works well within the wider system
Ability to translate business and product requirements into clear technical designs and working features, making effective use of AI tooling whilst owning the quality of the end result
Strong programming fundamentals in at least one modern programming language
An understanding of how to write code that performs well and scales reliably when processing high volumes of data
Have experience of the full engineering life cycle, from design and implementation through to testing and deployment
Passion and drive to grow within one of the UK’s fastest growing scale-ups
Experience in the following would be beneficial but not essential:
Commercial experience with Scala or Java, or Functional Programming experience in other languages
Working with big data technology, ideally Spark but others will also be useful such as Hadoop or Elasticsearch
Designing and building REST APIs (we take an OpenAPI spec-first approach)
Frontend development with Angular and TypeScript
Hands-on experience with agentic AI coding tools (e.g. Claude Code, Cursor, GitHub Copilot), such as using them to deliver features end-to-end or building custom workflows and integrations around them