Winston Fox
Senior Software Engineer
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We are hiring an exceptional Software Engineer for one of the world's leading technology-driven Hedge Funds. £400k - £600k
This is not a narrowly defined development role. You will work in a small, highly technical engineering team with significant ownership, sitting close to the investment business and building systems used directly by Traders, Quants, Treasury, Finance, and Operations.
The environment is deliberately flat. Engineers work directly with their users, challenge requirements, make architectural decisions, and take problems from an initial conversation through to production. There are very few layers between identifying a problem and building the solution.
As the fund continues to expand into new markets and asset classes, there is substantial greenfield engineering ahead. At the same time, the firm is pushing hard on the practical adoption of AI within Engineering, looking at how modern AI tooling and agentic workflows can materially improve the way software is designed, built, tested, understood, and operated.
The Engineering
You will design, build, and own software supporting some of the firm's most important financial workflows.
The role combines software engineering, distributed/data-intensive systems, financial markets, and direct business problem-solving. You will be expected to understand the problem rather than simply implement somebody else's specification. That could mean designing a new platform as the firm enters an asset class, working with Traders and Quants to understand a complex requirement, improving the architecture of an existing system, investigating a difficult production problem, optimizing a database and data pipeline operating at scale, or identifying where AI can remove engineering friction and automate previously manual development or operational workflows. This is an engineering role where ownership and execution matter.
You will:
- Own systems end-to-end, from requirements and architecture through development, testing, deployment, and production.
- Design and build new in-house platforms as the business expands into additional asset classes.
- Work directly with senior business users, turning complex financial problems into robust technical solutions.
- Write high-quality, testable production code and contribute directly to systems architecture.
- Engineer data-intensive applications requiring excellent SQL, database design, query optimization, and performance tuning.
- Build and improve ETL and data-loading architectures supporting complex financial datasets.
- Troubleshoot production systems and solve difficult reliability and performance problems.
- Help determine technical direction rather than simply working from predefined specifications.
- Actively explore and implement AI-assisted engineering workflows, using modern coding agents, LLM tooling, and automation to improve developer productivity, testing, debugging, code understanding, documentation, and operational support.
- Look beyond basic AI-assisted coding and identify opportunities to build agentic engineering workflows and internal tooling that can automate more complex parts of the software-development lifecycle.
- Help establish sensible engineering practices around AI-generated code, ensuring improvements in development speed do not come at the expense of testing, maintainability, security, or production quality.
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What We're Looking For
We are looking for a genuinely strong Software Engineer rather than somebody who simply matches a technology checklist.
You should have deep experience in an object-oriented engineering environment, ideally C#/.NET, together with exceptional SQL and database engineering skills.
You will also need experience building software around multiple financial products.
Critically, we want engineers who can demonstrate real project ownership. You should be able to talk in detail about systems you have personally taken from conception through architecture and implementation into production, the decisions you made along the way, and what happened when things went wrong.
Strong production troubleshooting skills and experience working directly with demanding business users are equally important.
We are also interested in engineers who are already thinking seriously about how AI changes Software Engineering. You don't need to be an ML Researcher, but you should be curious about modern AI development tooling and already experimenting with or implementing LLMs, coding agents, agentic workflows, or AI-driven automation as part of your engineering process.
The important thing is the mindset: we want engineers who see AI as an opportunity to increase the scope, speed, and quality of what a small, exceptional engineering team can deliver.
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Broader Technology
The environment is deliberately pragmatic rather than wedded to one technology. Engineers are expected to understand the underlying problem and choose the right tools.
Depending on the project, the wider technology landscape can include:
- C#/.NET
- Python
- Java
- Scala
- F#
- SQL
- Kafka
- Flink
- Kubernetes
- OpenShift
- Docker
- Helm
- Spark
- Hadoop
- Elasticsearch
- Neo4j
- Snowflake
- AWS Redshift
Experience with modern hardware architectures, cloud infrastructure, stream processing, Big Data/NoSQL technologies, or modern web frameworks such as React, Vue, or Angular would all be valuable.
Exposure to LLMs, coding agents, AI-assisted development environments, MCP, agent orchestration, or the implementation of internal AI engineering tools would be particularly interesting.
Why This Role?
The attraction is not simply the technology stack.
It is the opportunity to join an environment where strong engineers are trusted with difficult problems and given the autonomy to solve them.
You will work with highly capable colleagues and sophisticated users, operate close to the commercial decisions of the fund, and have genuine visibility of the impact of what you build.
The firm also believes that AI will materially change the way high-performance engineering teams operate. Rather than treating AI as a separate innovation project, the ambition is to embed it into day-to-day Engineering and give talented developers the freedom to find practical ways of using it to automate repetitive work, shorten development cycles, improve reliability, and increase the amount an individual engineer can achieve.
There is no need to move away from engineering to increase your influence. This is an environment that values people who can combine technical depth, judgment, ownership, and execution while remaining hands-on.
For an engineer who enjoys understanding complex systems, challenging assumptions, and building software that matters, there are few environments with a better combination of technical difficulty, autonomy, AI adoption, and direct business impact.
We are looking for "exceptional" and a "demonstrable track record", with a highly competitive process.
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