AI Engineer at Electric Twin

You will join the Science team to bridge the gap between AI research and production engineering. By designing cognitive architectures and memory systems for LLM-driven agents, you will help build a platform that predicts human behavior with 95% accuracy, enabling global brands to conduct deep market research in seconds rather than weeks.

Why this role is remarkable:

• Work at the frontier of behavioral simulation with a platform that delivers insights 10,000x faster than traditional research, validated by research from the London School of Economics.
• Join a high-caliber team founded by the former Chief Adviser on Digital to the UK Prime Minister and backed by $14M from top-tier investors including Atomico, LocalGlobe, and Marc Andreessen.
• Direct impact on a product used by giants like News UK and Lebara, moving beyond static data to create dynamic, reasoning digital populations.

What you will do:

• Design and implement cognitive systems that provide AI agents with consistent personalities, reasoning capabilities, and advanced memory using RAG and chain-of-thought prompting.
• Conduct systematic experiments to validate synthetic agent behavior against real-world data, iterating on model architectures based on empirical performance.
• Build the scalable backend infrastructure and sophisticated prompting strategies required to deploy multi-agent simulations in enterprise production environments.

The ideal candidate:

• Possesses over 7 years of technical experience with at least 1 year of hands‑on expertise building complex applications with Large Language Models and agentic workflows.
• Demonstrates strong proficiency in Python and backend frameworks like FastAPI or Django, with a solid understanding of distributed systems and scalable architectures.
• Holds a degree in a quantitative field (CS, Math, Physics, or AI) and thrives in fast‑paced environments where research‑driven development meets pragmatic engineering.