Posted 6 months ago
AI Engineer
LondonHybridFull-time
AI Summary
An AI Engineer researches and builds systems to bring AI agents to life and scales the infrastructure for LLM-driven synthetic populations, balancing agent research with backend engineering.
About this role
The Role
As an AI Engineer you will be part of the wider technical team but positioned within Science.You’ll research and build the systems that bring our AI agents to life and you will work with engineering to scale the infrastructure that powers our LLM-driven synthetic populations.
You'll design agent cognitive architectures, implement context engineering and memory systems, while ensuring these AI systems can operate reliably at scale in production environments.
You'll design agent cognitive architectures, implement context engineering and memory systems, while ensuring these AI systems can operate reliably at scale in production environments.
This role balances AI agent research with backend engineering. It is ideal for research engineers who want to work directly with large language models to create realistic behavioural simulations, while building the robust infrastructure needed to deploy them in enterprise settings.
What You'll Do
There are three main areas that members of the science team focus on:
Research, Modelling and Experimentation: You will design and run systematic experiments to evaluate synthetic agent behaviour, test hypotheses about behavioural patterns, and iterate on model architectures based on empirical results and validation against real-world data.
LLM Product Engineering: You will build sophisticated prompting strategies, behavioural frameworks, and decision-making systems that enable agents to exhibit realistic human-like behaviour across diverse scenarios and demographics. You will combine this with client interactions to ensure product viability for the end customer.
Architecture & Development: Design and implement the cognitive systems that give AI agents consistent personalities, memory, and reasoning capabilities, using advanced LLM techniques like chain-of-thought prompting, RAG systems, and agentic tool use.
Who You Are
Essential Qualifications
models to solve complex problems.
Technical Skills
Personal Attributes
stakeholders.
better solutions when evidence supports it.
Skills
DjangoExperiment TrackingFastAPIFlaskHugging Face TransformersLangChainLLMPrompt EngineeringPyTorchRAG
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