Product Engineer

Amatra Ltd; Greater London; Hybrid; GBP 60,000 - 90,000; Full time

Job summary

Amatra Ltd in the United Kingdom is seeking a Product Engineer to design and build AI-powered features for the platform that elite sporting organisations rely on daily. You will work across the full stack—from data pipelines and LLM integrations to intuitive interfaces that present insights to users.

You will ship features quickly, collaborate with founders and customers, own quality from prototype to production, and iterate based on real usage while balancing pragmatic decisions.

Qualifications

• Strong engineering background in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science.
• Familiarity with AI/ML concepts and experience working with LLMs, embeddings, or similar technologies.
• Comfortable working across the stack, from backend to frontend to infrastructure, with a bias toward shipping and iterating over perfecting in isolation.

Responsibilities

• Build and ship AI-powered product features across the full stack, from data layer to UI, including LLM-based workflows such as prompt engineering, RAG, and model evaluation.
• Work closely with founders and customers to translate needs into working software.
• Own the quality and reliability of what you ship, from prototype to production.
• Move fast, make pragmatic technical decisions, and iterate based on real usage.

Skills

AI/ML concepts

Full stack development

Shipping-focused

Tools

LLMs

Embeddings

Prompt engineering

Job description

As a Product Engineer at Amatra you will design and build AI-powered features for the platform that elite sporting organisations rely on every day. This means working across the full stack, from data pipelines and LLM integrations to the interfaces that put insights in front of users.

Responsibilities

• — Build and ship AI-powered product features across the full stack, from data layer to UI, including LLM-based workflows such as prompt engineering, RAG, and model evaluation.
• — Work closely with founders and customers to translate needs into working software.
• — Own the quality and reliability of what you ship, from prototype to production.
• — Move fast, make pragmatic technical decisions, and iterate based on real usage.

Requirements

• — Strong engineering background preferred (but not required), in fields such as Computer Science, Mathematics, Software Engineering, Physics, and Data Science.
• — Familiarity with AI/ML concepts and experience working with LLMs, embeddings, or similar technologies. Knowledge of classical ML and statistical techniques is a bonus.
• — Comfortable working across the stack, from backend to frontend to infrastructure, with a bias toward shipping and iterating over perfecting in isolation.