Core AI Engineer in London

Core AI Engineer in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Design and build AI infrastructure that powers innovative financial solutions.
  • Company: G-Research, a leader in quantitative finance and AI technology.
  • Benefits: Competitive salary, annual bonus, 30 days leave, and comprehensive healthcare.
  • Other info: Inclusive culture with excellent career growth and monthly company events.
  • Why this job: Join a dynamic team shaping the future of finance with cutting-edge AI.
  • Qualifications: Strong skills in C#, Python, and Kubernetes; experience in distributed systems.

The predicted salary is between 60000 - 80000 £ per year.

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.

The Core AI team is a centralised infrastructure team within the AI Engineering department. We build, operate and scale the foundational platform that powers AI innovation across G‑Research, including on‑prem open model inference, model serving, AI developer experience tooling, centralised MCP servers and secure agent sandboxing. We provide the foundations that enable teams across the firm to innovate and deliver with confidence, working closely with our Applied AI team.

As an Engineer in Core AI, you will work across four key areas:

  • Infrastructure and serving – design, build and operate on‑prem model inference and serving platforms;
  • MCP server infrastructure – build and operate centralised MCP servers that provide secure, governed access to tools and data;
  • Security and sandboxing – design and implement infrastructure for safe execution of autonomous AI agents in a regulated environment;
  • Developer AI experience – improve developer experience through seamless integrations and user‑facing tools.

Key responsibilities of the role include:

  • Designing and operating model serving infrastructure, including inference pipelines and scheduling systems
  • Building and running centralised MCP servers, ensuring secure, reliable access to enterprise tools and data
  • Owning platform reliability, performance and scalability across Kubernetes‑based infrastructure, including observability, capacity planning and incident response
  • Building self‑service tooling and APIs to enable teams to provision and consume AI infrastructure independently
  • Integrating platform services with existing technology stacks, ensuring clear interfaces, monitoring and CI/CD
  • Evaluating and adopting open‑source technologies and applying emerging best practices to improve the platform

We value pragmatic engineers who combine deep infrastructure expertise with strong systems thinking and clear communication. You should enjoy building reliable, secure platforms at scale – the kind of foundations that hundreds of engineers and quants depend on daily without needing to think about.

Essential skills and experience:

  • Strong expertise in C# and Python, building distributed systems and platform‑level software
  • Deep Kubernetes expertise, including multi‑tenant cluster operations and platform extensions
  • Experience with Docker, Terraform and CI/CD in controlled or regulated environments
  • Strong understanding of distributed systems, including networking, storage, security and performance
  • Experience with model serving and inference infrastructure, including deployment, scaling and optimisation of open models
  • Clear communication skills, with ability to explain complex concepts and produce high‑quality technical documentation

Desirable skills and experience:

  • Experience with MCP or similar platform services
  • Familiarity with sandboxing and workload isolation technologies
  • Experience in quantitative finance or low‑latency systems
  • AWS experience particularly in hybrid environments
  • Experience with observability tooling such as Prometheus, Grafana or OpenTelemetry
  • Contributions to open‑source projects in relevant domains

Why join us?

  • 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

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 a special need that requires accommodation please let us know in the relevant section.

At G-Research, we are passionate about the intersection of finance, technology, and the future. We offer a dynamic, flexible and highly stimulating culture where world‑beating ideas are cultivated and rewarded. We are proud to employ some of the best people in their field and to nurture their talent in our collaborative working environment.

Core AI Engineer in London employer: Barlowe LLP

At G-Research, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among world-class researchers and engineers. Located in London, our team enjoys highly competitive compensation, generous annual leave, and a strong commitment to work/life balance, alongside unique perks like a dedicated barista bar and monthly company events. We are dedicated to employee growth, providing opportunities to work on cutting-edge security systems while ensuring an inclusive environment for all.

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Contact Details:

Barlowe LLP Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Core AI Engineer in London

Join Local Tech Meetups

Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Barlowe LLP or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!

Contribute to Open Source Projects

Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Barlowe LLP.

Tap into Online Developer Communities

Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Barlowe LLP.

Explore Job Boards Specifically for Tech Roles

Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Barlowe LLP that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!

We think you need these skills to ace Core AI Engineer in London

C#
Python
Distributed Systems
Kubernetes
Docker
Terraform
CI/CD

Some tips for your application 🫡

Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.

Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Barlowe LLP.

Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Barlowe LLP and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!

Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!

How to prepare for a job interview at Barlowe LLP

Brush Up on Your Coding Skills

For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.

Know Your Tools and Frameworks

Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Barlowe LLP uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.

Showcase Your Projects

Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.

Prepare for Behavioural Questions

While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.