Platform Engineer, Generative AI & LLM Systems

Scale; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Scale GP is building an enterprise-grade Generative AI platform. We seek a strong engineer to own large new areas, drive features end-to-end, and work across backend, frontend, and ML components.

You will develop reliable Python services, scale distributed systems, and integrate with LLMs and vector databases to power intelligent experiences. Ideal candidates have 4+ years of engineering experience, familiarity with AI tooling, and cloud exposure.

Qualifications

• 4+ years of full-time engineering experience.
• Experience scaling or shipping products at high-growth startups.
• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling.
• Proficiency with SQL and modern API development.
• Experience with Kubernetes, containerization, and microservice architectures.
• Experience working with at least one major cloud provider.

Responsibilities

• Own large new areas within our product, driving features from design through production deployment.
• Work across backend, frontend, and interacting with LLMs and ML models
• Develop reliable backend services in Python, working with distributed systems, data pipelines, and ML/LLM components.
• Integrate with LLMs, vector databases, and AI infrastructure to power intelligent product experiences.
• Deliver experiments and new features quickly, maintaining high quality and tight feedback loops with customers.
• Collaborate across product, ML, and infrastructure teams to shape the direction of Scale GP.

Skills

Python

Distributed systems

SQL

Kubernetes

Cloud platforms

Tools

LLMs

Job description

Scale GP is building an enterprise-grade Generative AI platform. We seek a strong engineer to own large new areas, drive features end-to-end, and work across backend, frontend, and ML components.

You will develop reliable Python services, scale distributed systems, and integrate with LLMs and vector databases to power intelligent experiences. Ideal candidates have 4+ years of engineering experience, familiarity with AI tooling, and cloud exposure.