Software Engineer, Platform (AI)

TL;DR

Software Engineer, Platform (AI): Building and scaling an enterprise-grade Generative AI platform with an accent on knowledge retrieval, inference, and evaluation. Focus on designing reliable backend services, integrating LLMs and vector databases, and solving complex scalability and reliability challenges.

Location: London, UK

Company

Scale AI develops reliable AI systems and provides high-quality data and full-stack technologies to power the world's leading models for enterprises and governments.

What you will do

• Own large new product areas, driving features from initial design through to production deployment.
• Develop and maintain reliable backend services in Python, focusing on distributed systems and data pipelines.
• Integrate LLMs, vector databases, and AI infrastructure to create intelligent product experiences.
• Work across the full stack, including frontend development and interaction with ML models.
• Collaborate with product, ML, and infrastructure teams to shape the direction of the Scale GP platform.
• Deliver experiments and new features rapidly while maintaining high quality and tight customer feedback loops.

Requirements

• 4+ years of full-time engineering experience post-graduation.
• Strong proficiency in Python or Javascript/Typescript.
• Experience scaling or shipping products within high-growth startup environments.
• Proficiency with SQL and modern API development.
• Experience with Kubernetes, containerization, and microservice architectures.
• Experience with at least one major cloud provider (AWS, GCP, or Azure).

Nice to have

• Familiarity with LLMs, vector databases, embeddings, or other modern AI tooling (production or tinkering experience).

Culture & Benefits

• Mission-driven environment focused on developing AI for the world's most important decisions.
• Inclusive and equal opportunity workplace committed to diversity.
• Opportunity to work with industry leaders across government and private sectors.
• Fast-paced environment with a focus on rapid learning and technology adaptation.