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 roleWe are building the AI layer that will transform how teams across the firm work, from quant research to engineering, risk and operations.
The Applied AI team sits at the centre of this effort. We are a small, high-autonomy team focused on defining how AI should be used across the entire company and delivering it in practice.
We own a number of large high-impact projects end-to-end. We also embed with teams across the firm when needed, partnering with quantitative researchers to build tools that accelerate discovery, taking promising prototypes from engineering teams and scaling them for firm-wide use, or working with corporate functions to automate a workflows.
Key responsibilities of the role include:
- Working across areas such as retrieval and knowledge systems, multi-agent orchestration, evaluation and reliability and context engineering
- Taking AI systems from early prototypes to trusted, production-ready solutions
- Owning high-impact projects from initial concept through to production
- Partnering with teams across the firm to identifying problems and delivering scalable solutions
- Turning team-specific use cases into solutions that can be adopted more widely across the organisation
You are a strong software engineer who actively builds with modern AI technologies. You have experience delivering LLM-powered systems in production and understand how to design, evaluate and operate them effectively.
The ideal candidate will have the following skills and experience:
- Hands-on experience building with LLMs in production, including agents, RAG pipelines, MCPs, tool-use, multi-step workflows. You've used frameworks like LangGraph, Pydantic AI or similar, and you know when to use them and when to throw them away
- Strong Python engineering skills. Clean, testable, production-quality code
- Experience with context engineering, including retrieval strategies, prompt construction, information routing, memory
- Experience with evaluation and observability for AI systems. Measuring accuracy, detecting regressions, understanding failure modes
- The ability to work across domains. You're comfortable embedding with a quant research team one month and an ops team the next
- Clear communication
- Fine-tuning or adapting foundation models, such as LoRA and DPO
- Comfort integrating with heterogeneous stacks, such as C#, C++, JVM, gRPC, Kubernetes
- Contributions to open-source AI projects, technical writing or conference talks.
We're looking for people who want to shape how an entire organisation works with AI. If that's you, we'd love to talk.
Why join us?
- Highly competitive compensation plus annual discretionary bonus
- Lunch provided (via Just Eat for Business) and dedicated barista bar
- 35 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
G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.
We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section
