AI Engineer at Electric Twin

You will research and build cognitive architectures for AI agents that simulate human populations with 95% accuracy. Balancing LLM experimentation with backend engineering, you’ll develop memory and reasoning systems validated by London School of Economics research, enabling global brands to predict audience responses to messaging and products in seconds.

• Design and implement cognitive systems for AI agents using advanced LLM techniques including RAG, chain-of-thought prompting, and agentic tool use.
• Run systematic experiments to validate synthetic agent behavior against real-world data, iterating on behavioral frameworks for diverse demographics.
• Build and scale the backend infrastructure using Python and FastAPI to deploy these realistic simulations in production for enterprise clients.

• Possesses a strong research background in human behavior, cognitive modeling, or agent-based social simulation paired with robust backend engineering skills.
• Has over 7 years of technical experience with at least 1 year of hands-on experience building production-grade LLM applications and multi-agent systems.
• Demonstrates an ownership mentality and technical proficiency in Python, PyTorch, and LangChain to move projects from hypothesis to deployment.

• Work on world-first technology validated by the London School of Economics that delivers human insights 10,000x faster than traditional research methods.
• Backed by a $14M investment from top-tier VCs like Atomico and LocalGlobe, alongside elite angels including Marc Andreessen and the CTO of Slack.
• Founded by a former Chief Adviser to the UK Prime Minister and a military commander, offering unique leadership at the intersection of data science and high-stakes decision making.