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Software Engineer

  • Software Engineering
  • London

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.

From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve.  Together we’re building a world-class platform to amplify our teams’ most powerful ideas.

As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.

Take the next step in your career.

The role

We are looking for Software Engineers to join our Core AI subteam within the AI Engineering Group.

The team’s mission is to build, operate and continuously evolve the core platforms that power every GenAI initiative across GResearch, from RAG services used by the entire company to improving developer experience by introducing new tools, commercial or custom built, to our quants and engineers.

As a member of the Core AI you will design and deliver scalable, reliable and secure services and tooling that enable researchers, data scientists and application teams to develop, deploy and monitor AI solutions quickly and safely.

As a Software Engineer, your work will span building distributed systems, LLM orchestration and inference, LLM integration with internal systems and deploying the latest third party AI technologies internally.

Key responsibilities of the role include:

  • Designing, building and operating platform services in C# and Python that provide common capabilities such as feature stores, vector search, prompt management and model hosting

  • Implementing orchestration workflows with tools such as LangGraph and Pydantic‑based data models to ensure type‑safe, auditable pipelines

  • Integrating and scaling RAG technologies to support huge embedding workloads

  • Collaborating with product and research teams to turn cutting‑edge prototypes into robust, production‑grade services

  • Championing engineering best practices, including version control, automated testing, CI/CD and  observability, and embedding them into every platform component

  • Benchmarking and optimising latency, throughput and cost across on‑prem GPU clusters and cloud environments

  • Influencing G‑Research’s AI strategy by evaluating vendor products, open‑source projects and industry trends, and advising on build‑vs‑buy decisions

  • Coaching and upskilling engineers across the firm in using platform APIs, SDKs and self‑service tooling effectively.

Who are we looking for?

We value engineers who thrive on solving hard problems, enjoy working in polyglot codebases and care deeply about developer experience.

You should be comfortable owning a service end‑to‑end, from design docs to production dashboards, and excited by the prospect of shaping the foundation on which every AI workload at G‑Research runs.

The ideal candidate will have the following skills and experience:

  • Degree in Computer Science, Engineering or a related field, or equivalent professional experience.

  • Strong, production‑grade programming skills in C# and Python or similar languages

  • Solid understanding of distributed systems concepts, such as networking, storage, concurrency and fault tolerance

  • Familiarity with modern AI engineering tooling and patterns, such as LangGraph/LangChain, Pydantic, FastAPI, MCP, RAG pipelines and agentic workflows

  • Proven track record of delivering high‑availability services and automating their testing and deployment, including Git, Docker, Kubernetes and CI/CD

  • Ability to translate abstract requirements into secure, scalable technical designs and to communicate those designs clearly

Desirable:

  • Exposure to GPU scheduling, model‑parallel inference frameworks. Such as  vLLM or TensorRT‑LLM, or serving LLMs in production

  • Experience operating hybrid on‑prem and cloud (AWS, Azure, GCP) environments at scale

  • Knowledge of performance‑critical programming, low‑latency networking or high‑frequency data processing

  • Contributions to open‑source AI infrastructure projects

Why should you apply?

  • Highly competitive compensation plus annual discretionary bonus

  • Lunch provided (via Just Eat for Business) and dedicated barista bar

  • 30 days’ annual leave

  • 9% company pension contributions

  • Informal dress code and excellent work/life balance

  • Comprehensive healthcare and life assurance

  • Cycle-to-work scheme

  • Monthly company events

Location: London
Apply Now
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What our people say

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Alexander Software Engineer

"I've felt very lucky to work with teams of people across the business who are generous with their time, knowledge and ideas as we collaborate to continuously build and rebuild complex systems with lots of moving parts."

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Dexter Software Engineer

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Owen Software Engineer

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Matteo Quantitative Research Intern

"One of the things that has truly stood out to me is the collaborative and welcoming culture. I hadn’t expected such a supportive environment but it’s been one of the main reasons I’ve enjoyed working here from day one."

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Margot HRIS manager

"I enjoy how dynamic the work environment at G-Research is. It keeps you busy and continuously creates opportunities to develop yourself and your career, too."

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Mario FPGA Manager

"While some people might think working in finance may not be too exciting, at G-Research, it is, especially if you see it as a problem to solve. How do we solve this algorithm? How do we get faster? This is why I think people are really excited to work here."

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Simon Cyber Security Manager

"There are lots of people within the business that have started as a junior and progressed – which I think is testament to G-Research's belief in fostering growth and recognising potential."

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Sebastian Senior Quantitative Researcher

"G-Research makes a lot of effort to have a very open culture and gives a lot of freedom to its individual researchers to pursue directions that they think are valuable, with each researcher very much driving their own research. I didn’t feel like I was losing a lot of freedom compared to academia."

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Mia Software Engineer

"What I appreciate most about working in G-Research is the supportive and knowledgeable environment. Everyone is incredibly helpful and patient, which ensures there’s a good balance between being challenged and your workload."

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Yang Quantitative Researcher

"What I like the most about my job is it’s super open. I’m able to work with a lot of folks from other teams, too, such as working closely with engineers and other quantitative researchers."

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Interview process

Online Application

Our assessment process kicks off with our Talent Acquisition team, who will review your application and assess your fit for the role.

Stage One: Technical Interview

You will meet with a team member – or take a remote test – where your technical abilities will be put to the test.

Stage Two: Behavioural Interview

We will set aside technical skills and focus on you.

Stage Three: Further Technical Interviews

Here, we will take a deeper dive into your technical skills and competencies.

Stage Four: Management Interviews

The final stage of our interview process is where you will meet members of your team, your future manager, and functional leadership.

Software Engineer Apply now

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