Artificial Intelligence Engineer

Formula.; Greater London; Hybrid; GBP 70,000 - 110,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Formula. is seeking an AI Engineer to design, build, deploy and monitor AI systems in production. You will work in a cross-functional team with product, data and platform engineers, delivering high-quality software at a frequent cadence.

You'll own the full lifecycle, choose efficient solutions, and balance performance with cost. The role is hybrid and based in London, with a competitive package and benefits.

Qualifications

• Experience with Gen AI tools (LangGraph, CrewAI, Hugging Face or OpenAI) and ML frameworks like PyTorch or TensorFlow.
• Strong understanding of ML fundamentals and LLM challenges (prompt engineering, latency, cost).
• Experience with cloud platforms (AWS, GCP or Azure) and infrastructure-as-code (Terraform).
• Hands-on with DevOps practices (CI/CD, Docker, Kubernetes) and observability tools (Prometheus, Grafana, Datadog).
• Experience with distributed systems, scaling, and both SQL and NoSQL datastores.
• Fluent in English to C2 level.
• Real ownership of AI systems in production.
• Hands-on, full-lifecycle engineering culture.
• Hybrid working based in London.

Responsibilities

• Design, build, deploy and monitor AI systems that scale across the business.
• Work in a cross-functional team with product, data and platform engineers, releasing software frequently.
• Own quality through rigorous automated testing, metrics and observability.
• Assess and select the right solution for each task, balancing performance, cost and delivery timelines.
• Build and optimise systems for performance, scalability and reliability.

Skills

Gen AI tools

ML fundamentals

LLM optimization

Cloud platforms

CI/CD

Observability

Distributed systems

SQL & NoSQL

English fluency (C2)

Ownership of production AI systems

Cross-functional collaboration

Full-lifecycle engineering

Hybrid/London-based

Tools

Terraform

Docker

Kubernetes

PyTorch

TensorFlow

Job description

We're working with an established technology and services business to find an AI Engineer who will help design, build, deploy and monitor AI systems in production. This is an AI Engineer role for someone with a real curiosity for AI and a firm grounding in software engineering, who wants their work shipping to real users rather than sitting in a proof of concept. You'll sit in a cross-functional team alongside product, data and platform engineers, releasing high-quality software to a frequent cadence.

The team is hands-on across the full lifecycle, owning what they build all the way through to running it in production. You'll help pick the right approach for each problem, keep an eye on cost and timelines, and make sure what ships is well tested and reliable.

Responsibilities as an AI Engineer:

• Design, build, deploy and monitor AI systems that scale across the business
• Work in a cross-functional team with product, data and platform engineers, releasing software frequently
• Own quality through rigorous automated testing, metrics and observability
• Assess and select the right solution for each task, balancing performance, cost and delivery timelines
• Build and optimise systems for performance, scalability and reliability

Requirements:

• Experience with Gen AI tools (such as LangGraph, CrewAI, Hugging Face or OpenAI APIs) and ML frameworks like PyTorch or TensorFlow
• Strong understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges such as prompt engineering, latency and cost optimisation
• Experience with cloud platforms (AWS, GCP or Azure) and infrastructure-as-code such as Terraform
• Hands-on with DevOps practices (CI/CD, Docker, Kubernetes) and observability tools like Prometheus, Grafana or Datadog
• Experience with distributed systems, scaling, and both SQL and NoSQL datastores
• Agentic workflow experience (autonomous or multi-agent systems) is a plus, and this AI Engineer role suits one who is fluent in English to C2 level
• Real ownership of AI systems in production
• A hands-on, full-lifecycle engineering culture where you build it and run it
• Work across modern AI tooling, cloud and agentic architectures
• A cross-functional team with strong product, data and platform peers to learn from
• Hybrid working based in London
• Competitive package and benefits (to confirm with the client)

If you're an engineer who wants to build real AI products at scale, this AI Engineer role is worth a conversation. Bring the software fundamentals and the appetite to learn fast, and you'll ship work that reaches people every day.

**Due to the high volume of applications, not all applicants will receive feedback.