Core AI Engineer

Overview

As part of the Core AI team in our AI Engineering department, you design and operate foundational platforms for AI innovation at G-Research. You will build scalable, secure infrastructure for on‑prem model inference, serving, and developer tooling, enabling hundreds of engineers and quants to work confidently. You’ll own reliability, performance, and observability across Kubernetes-based systems and contribute to a safe, regulated environment through sandboxing. This role offers the opportunity to shape the core infra that powers cutting‑edge research and collaboration across the firm.

Pay / Benefits

• competitive compensation
• annual discretionary bonus
• lunch provided
• 30 days annual leave
• 9% pension contributions
• healthcare and life assurance

Responsibilities

• Design and operate model serving infrastructure, including inference pipelines and scheduling systems
• Build and run centralised MCP servers for secure access to tools and data
• Own platform reliability, performance, and scalability across Kubernetes-based infrastructure (observability, capacity planning, incident response)
• Develop self-service tooling and APIs to enable autonomous provisioning of AI infrastructure
• Integrate platform services with existing tech stacks, ensuring clear interfaces, monitoring, and CI/CD
• Evaluate and adopt open-source technologies and apply best practices to improve the platform

Key requirements

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

• Clear communication
• Pragmatism and systems thinking
• Ability to work at scale and collaborate with cross-functional teams
• C#
• Python
• Kubernetes

…