Data & Analytics - Gen AI Engineers x 2

Data & Analytics - Gen AI Engineers x 2

Posted 1 day ago by CBS Butler

£525 Per day
Inside
Remote
Farnborough, UK

Summary: The role involves designing, prototyping, and deploying Generative AI models for enterprise applications. The position requires collaboration with architects to create scalable AI service architectures and the integration of AI models with existing systems. Candidates will also be responsible for managing AI/ML pipelines and ensuring compliance with ethical standards. This is a fully remote contract position for an initial duration of six months.

Key Responsibilities:

  • 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.

Key Skills:

  • Design of Gen AI Models
  • RAG
  • AI/ML Pipelines
  • 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 (eg, 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.

Salary (Rate): £525 per day

City: Farnborough

Country: UK

Working Arrangements: remote

IR35 Status: inside IR35

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

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 (eg, 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.