Overview
The Senior Applied AI Engineer will play a crucial role in a rapidly scaling UK deep-tech company by leading the architecture and development of advanced agentic AI systems for commercial applications in biotech and pharma. This contract position allows for significant influence over system design and delivery within the AI team, requiring deep technical expertise and a hands-on approach to software engineering. The role promotes a hybrid work model, with part of the week spent on-site, and offers a competitive day rate that reflects the seniority of the position.
Responsibilities
- Architect and build end-to-end multi-agent AI systems using various frameworks and bespoke orchestration designs.
- Write robust production-grade code focused on reliability, latency, and graceful failure.
- Embed large language models and vision-language models into live workflows for reasoning, search, summarization, and task execution.
- Deploy AI systems across cloud and on-premises environments, tailoring approaches to respective security and connectivity constraints.
- Take ownership of production pipelines from data ingestion to live inference.
- Build monitoring and evaluation tools to assess system performance in real-time.
- Establish technical standards and documentation for agentic AI within the engineering team.
Requirements
- Extensive experience in robust software engineering with a focus on LLM-powered or agentic systems at a senior/lead level.
- Strong Python programming skills with proficiency in frameworks such as LangGraph, LangChain, or Haystack.
- Demonstrated success in building and maintaining multi-agent AI systems in live production environments.
- Real-world experience in deploying AI/ML systems beyond proof-of-concepts and notebooks.
- Knowledge of data pipeline design, inference performance, and state/memory handling.
- Familiarity with Docker, Git, and cloud infrastructure, particularly AWS.
- Understanding of secure deployment methodologies, including on-premises and sovereign cloud constraints.