Agentic AI Lead Location: London or Edinburgh - Hybrid - 2 days per week onsite Start day: ASAP Contractor rate: TBC, likely in the region of £500 per day inside IR35 Duration: 6 to 12 months initially Role Overview Our client is seeking a hands‑on Agentic AI Lead to design and deliver production‑ready AI and machine learning solutions using Python and AWS. This role is focused on building intelligent, scalable AI services, including Agentic AI, NLP, and retrieval‑based systems, combining strong software engineering with modern ML and Generative AI practices. Key Responsibilities \* Build and deploy machine learning and NLP solutions using Python, scikit‑learn, SciPy, and PyTorch \* Develop and productionise models on Amazon SageMaker \* Design API‑first, microservices‑based AI systems with async, event‑driven patterns and data pipelines \* Build rapid prototypes and AI applications using FastAPI, Streamlit, Matplotlib, and Seaborn \* Develop intelligent retrieval pipelines using vector databases (e.g. FAISS) and semantic search \* Create Agentic AI solutions using frameworks such as LangChain, LangGraph, and ReAct \* Apply clustering and classification techniques to support ML use cases \* Maintain high standards of code quality, testing, and TDD‑driven development Essential Skills & Experience Extensive hands-on experience of frameworks and libraries: \* Proficient in scikit-learn and SciPy for ML algorithms. \* Hands-on experience within python with PyTorch and experience in developing enterprise python applications. \* Skilled in natural language processing tasks (entity recognition, tokenization). \* Strong knowledge of API/Microservices, Async programming, multithreading, performance, reliability, caching, event driven design, data pipelines, workflows, queues. \* Hands-on with Amazon SageMaker for building, training, and deploying scalable machine learning models in cloud. \* Experience of Building rapid applications using FastAPI and Streamlit, Matplotlib, seaborn enabling prototyping. \* Good understanding of Software Engineering, Architecture, testing, code quality principles and test driven development (TDD). Generative AI & LLMs \* Proficient in context-aware prompts to drive optimal performance from LLMs for summarization, reasoning, extraction, and classification tasks. \* Hands-on experience in designing intelligent retrieval pipelines that combine vector databases like FAISS with semantic search mechanisms. \* Should have Developed intelligent agents capable of reasoning, planning, and tool use by leveraging frameworks such as ReAct, LangChain/Langgraph. \* Experience of Clustering techniques and classification models If you have the relevant skills and experience, please do apply promptly to be considered