Data & Analytics - Gen AI Engineers x 2

CBSbutler Holdings Limited trading as CBSbutler; England; Remote; GBP 80,000 - 100,000; Full time

Job summary

A tech recruitment company is seeking experienced Gen AI Engineers for a fully remote contract in the UK. Responsibilities include designing and deploying AI models for enterprise applications, optimizing performance, and collaborating with stakeholders to define AI use cases. The ideal candidates will have experience with AI/ML pipelines and be proficient in languages such as Python, Java, or Node.js.

Qualifications

• Experience designing and deploying Generative AI models.
• Proficiency in optimizing AI model performance.
• Familiarity with compliance in AI ethics and governance.

Responsibilities

• Design, prototype, and deploy Generative AI models.
• Build and fine-tune LLM-based applications.
• Collaborate with architects on scalable AI service architectures.

Skills

Design of Gen AI Models

AI/ML Pipelines

Prompt Engineering

Integrating AI Models

Tools

MLflow

Vertex AI

Azure ML

Python

Java

Node.js

Vector Databases

Job description

Data & Analytics - Gen AI Engineers x 2

+ fully remote contract

+ initially 6 months

+ 500 to 525 per day - Inside IR35

Key Skills

+ Design of Gen AI Models

+ RAG

+ AI/ML Pipelines

The Role

+ Design, prototype, and deploy Generative AI models (LLMs, Transformers, Diffusion models) for enterprise use cases.

+ Build and fine-tune LLM-based applications (chatbots, summarization, document Q&A, report generation, code assistants, etc.).

+ Apply prompt engineering, RAG (Retrieval-Augmented Generation), and context-aware pipelines to ensure accuracy and relevance.

+ Integrate AI models with enterprise systems, APIs, and data stores using Python, Java, or Node.js backends.

+ Collaborate with architects to define scalable and secure AI service architectures.

Required Experience/Skills

• Implementing AI/ML pipelines for model training, validation, and deployment (using tools such as MLflow, Vertex AI, or Azure ML).
• Manage model evaluation, drift monitoring, and continuous improvement processes.
• Optimize inference performance and cost (e.g., model compression, quantization, API optimization).
• Ensure compliance with AI ethics, security, and governance standards.
• Prepare and curate training datasets (structured/unstructured text, images, code).
• Apply data preprocessing, tokenization, and embedding generation techniques.
• Work with vector databases (Pinecone, Weaviate, FAISS, Chroma) for semantic retrieval use cases.
• Partner with business stakeholders to identify and shape AI use cases.
• Contribute to the creation of a strategic AI adoption roadmap and reusable AI Workbench / platform components.
• Support POCs, pilots, and full-scale implementations with agile delivery.