AI Infrastructure Lead

AI Infrastructure Lead - Build Our In-House AI Environment

Location: London, Bank (onsite)
Type: Full-time | Permanent
Salary: Competitive + Benefits

About Us
We're an ambitious technology company using advanced Machine Learning (ML) and Natural Language Processing (NLP) to power next-generation products. Until now, our AI projects have relied on third-party engines deployed via Docker - but it's time to take the next step. We're ready to build our own in-house AI environment, giving us full control over our models, data, and innovation pipeline.

To make that happen, we're looking for an AI Infrastructure Lead - someone with the technical depth and vision to architect, implement, and scale an environment capable of supporting multiple ML and NLP initiatives across the business.

The Role
As our first senior AI hire, you'll take ownership of designing and building the foundation of our AI ecosystem. You'll shape the infrastructure strategy, establish our MLOps pipelines, and work closely with product and data teams to enable seamless model development and deployment. Once the environment is established, you'll play a key role in recruiting and mentoring two mid-level AI engineers who will join your team.

Responsibilities

• Architect, build, and maintain an in-house AI environment (on-prem or hybrid cloud).
• Design MLOps workflows for training, deploying, and monitoring models.
• Integrate and manage containerized AI engines (Docker/Kubernetes).
• Establish best practices for model versioning, data pipelines, and reproducibility.
• Collaborate with ML and NLP researchers to optimize infrastructure for experimentation.
• Set up CI/CD pipelines, monitoring tools, and scalable compute infrastructure.
• Lead future recruitment and mentoring of additional AI engineers.

Requirements

• Proven experience in AI/ML infrastructure, DevOps, or MLOps engineering.
• Strong understanding of machine learning workflows, model deployment, and data pipelines.
• Expertise with Docker, Kubernetes, and cloud services (AWS, Azure, or GCP).
• Familiarity with NLP frameworks (e.g., Hugging Face, spaCy, LangChain) is a plus.
• Experience setting up and maintaining GPU-accelerated compute environments.
• Solid coding background (Python preferred).
• Ability to lead projects from concept to delivery in a fast-paced, collaborative environment.

What We Offer

• Opportunity to design and own the company's AI infrastructure from the ground up.
• Work with cutting-edge AI technologies in a hands-on, high-impact role.
• Leadership path - build your own AI engineering team.
• Competitive salary, flexible working, and professional growth opportunities.

Ready to build the foundation of our AI future?
Apply now and help us shape an intelligent, scalable, and independent AI ecosystem.