Applied AI Engineer

The Role

We 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 workflows.

Key Responsibilities

• 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 identify problems and deliver scalable solutions
• Turning team-specific use cases into solutions that can be adopted more widely across the organisation

Who Are We Looking For?

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.

Essential 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

Nice to Have

• 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

Our Benefits

Finance

• Highly competitive compensation plus annual discretionary bonus
• 9% company pension contributions
• Season ticket loan
• Give as you Earn (GAYE)
• Risk protection benefits
• Charity fundraising matching scheme
• Generous relocation and immigration assistance

Health

• Comprehensive private health insurance, including GP access, dental and vision
• Enhanced health support for male and female health, fertility, family forming, maternity and menopause journeys
• Healthcare cash plan covering a wide range of routine and complimentary healthcare expenses
• Employee Assistance and Wellness Programmes

Lifestyle

• 35 days annual leave (30 base days, plus 5 additional for office-based staff)
• Enhanced leave policies to support people and their family needs
• Back-up dependent care for children, adults and pets
• Complimentary travel insurance for people and their families
• Cycle-to-work scheme
• Gym and Fitness membership subsidies
• Lunch provided (via Just Eat for Business) and dedicated barista bar
• Regular company socials
• Informal dress code and excellent work-life balance
• Talks from world-class guest speakers

About G-Research

G-Research is a leading quantitative research and technology firm. From offices in London and Dallas, the company brings together world-class researchers and engineers in a collaborative culture that values deep exploration, methodical execution, and long-term thinking. The firm applies scientific rigor, advanced machine learning, and cutting-edge technology to tackle complex problems in finance and predict movements in global markets.

Location: London. Department: Software Engineering.