Infrastructure Testing Specialist in London

Fin is the AI Customer Agent company on a mission to help businesses provide perfect customer experiences. Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey - from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration.

Founded in 2011, Fin became one of the fastest growing companies and remains one of the largest private software companies in the world with nearly 30,000 global businesses using our products to transform their customer support. We’re looking for Senior+ AI Infrastructure Engineers to build the systems that train and serve Fin's next generation of AI products.

You’ll join a small, highly technical team working at the cutting edge of modern AI infrastructure. The AI Infra team built the training pipelines and runs the inference for custom models like Fin Apex, which outperforms frontier models in customer service tasks, and is the foundation of the AI Group's full stack approach to AI.

As a Senior AI Infrastructure Engineer focused on model training and inference, you will:

• Implement and scale training pipelines for large transformer and LLM models, from data ingestion and preprocessing through distributed training and evaluation.
• Work on GPU‑level performance: tuning kernels, improving utilization, and identifying bottlenecks across our training and inference stack.
• Collaborate closely with ML scientists to implement cutting edge training and inference methods and bring them to production.
• Raise the bar for technical standards, reliability, and operational excellence across Fin's AI platform.

We’re looking to hire Senior+ AI Infrastructure Engineers. You’re likely a great fit if:

• You have 5+ years of experience in software engineering, with a strong track record of shipping high‑quality products or platforms.
• You hold a degree in Computer Science, Computer Engineering, or a related field (or you have equivalent experience with very strong fundamentals).
• Model training (especially transformers and LLMs).
• Low‑level GPU work, such as writing CUDA or Triton kernels.
• Comfortable working in production environments at meaningful scale (traffic, data, or organizational).
• Have deep knowledge of at least one programming language (for example Python, Ruby, Java, Go, etc.). Specific language experience is less important than your ability to write clean, reliable code and learn new stacks quickly.

Bonus skills & attributes:

• Experience at AI native companies that train and/or run inference for their own models (e.g. modern AI labs or AI‑native product companies).
• Experience running training or inference workloads on Kubernetes.
• Experience with AWS or other major cloud providers.
• Production experience with Python in ML or infrastructure contexts.
• Demonstrated passion for technology through personal projects, open source, meetups, or publishing content about your work and learnings.

Benefits:

• Competitive salary and equity in a fast-growing start-up.
• We serve lunch every weekday, plus a variety of snack foods and a fully stocked kitchen.
• Regular compensation reviews - we reward great work!
• Unlimited access to Claude Code and best-in-class AI tools; experimentation & building is encouraged & celebrated.
• Pension scheme & match up to 4%.
• Peace of mind with life assurance, as well as comprehensive health and dental insurance for you and your dependents.
• Flexible paid time off policy.
• Paid maternity leave, as well as 6 weeks paternity leave for fathers, to let you spend valuable time with your loved ones.
• If you’re cycling, we’ve got you covered on the Cycle-to-Work Scheme. With secure bike storage too.
• MacBooks are our standard, but we also offer Windows for certain roles when needed.

Policies:

Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.

As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. Fin values diversity and is committed to a policy of Equal Employment Opportunity. Fin will not discriminate against an applicant or employee on the basis of race, color, religion, creed, national origin, ancestry, sex, gender, age, physical or mental disability, veteran or military status, genetic information, sexual orientation, gender identity, gender expression, marital status, or any other legally recognized protected basis under federal, state, or local law.