Do you want to tackle the biggest questions in finance with near infinite compute power at your fingertips?
G-Research is a leading quantitative research and technology firm, with offices in London and Dallas.
We are proud to employ some of the best people in their field and to nurture their talent in a dynamic, flexible and highly stimulating culture where world-beating ideas are cultivated and rewarded.
This is a role based in our new Soho Place office – opened in 2023 - in the heart of Central London and home to our Research Lab.
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 G‑Research, 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
