Agentic AI Lead

Queen Square Recruitment
London, United Kingdom
Last month
£500 pd
Applications closed

Related Jobs

View all jobs
Spotlight

Senior ML Runtime Engineer

Fractile London, United Kingdom
Spotlight

Senior ML Compiler Engineer

Fractile Bristol, United Kingdom

AI & Surge Enablement Lead, EMEA Field Enablement Team, WWFE - EMEA Field Enablement

Amazon London, United Kingdom
On-site

Principal AI scientist - Perm- UK

Infused Solutions United Kingdom
£110,000 – £125,000 pa Remote

Head of AI & Automation

Experis United Kingdom
£85,000 – £100,000 pa Hybrid

Senior ML Engineer, Dubbing

Synthesia London, United Kingdom
Remote

Senior Solutions Architect, Generative AI - AI Models and Systems at NVAITC

NVIDIA Cambridge, United Kingdom
On-site

Senior Solutions Architect, Generative AI - AI Models and Systems at NVAITC

NVIDIA Reading, United Kingdom
On-site

Salary

£500 pd

Job Type
Contract
Work Location
Hybrid
Seniority
Lead
Education
Degree
Posted
29 Apr 2026 (Last month)

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

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Where to Advertise Machine Learning Jobs in the UK (2026 Guide)

Where to advertise machine learning jobs UK in 2026: the specialist boards and communities that reach ML, MLOps and deep learning engineering talent. The candidate pool is small, highly specialised and in demand across AI labs, financial services, healthcare, autonomous systems and consumer technology simultaneously. Machine learning engineers and researchers move between roles through professional networks, conference communities and specialist platforms — not general job boards where ML roles compete with unrelated software engineering positions for the same audience. This guide, published by MachineLearningJobs.co.uk, covers where to advertise machine learning roles in the UK in 2026, how the main platforms compare, what employers should expect to pay, and what the data says about hiring across different role types.