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Generative AI Engineer

Job in Leeds, West Yorkshire, ME17, England, UK
Listing for: Avensys Consulting UK
Full Time position
Listed on 2025-12-30
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 450 - 500 GBP Daily GBP 450.00 500.00 DAY
Job Description & How to Apply Below

Role: Gen AI Engineer

Location: Remote

Contract: 06 Months

Rate: 450-500 GBP Per Day – Inside IR35 MAX

The Gen AI Engineer will be a specialized type of artificial intelligence professional, focused on designing, developing & implementing generative AI models and algorithms. Working collaboratively with the team to ensure project deadlines are met.

  • 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.
Experience in the following
  • 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.
  • Document and present solution designs, technical findings, and results to leadership and clients.
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