AI Engineer

What we're looking for

• Design, build, and deploy Generative AI solutions using Large Language Models (LLMs).
• Develop AI applications such as chatbots, virtual assistants, search assistants, summarization tools, and content generation platforms.
• Work with foundation models such as GPT, Claude, Gemini, Llama, Mistral, or similar models.
• Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases and embedding models.
• Build prompt engineering frameworks and optimize prompts for better accuracy and performance.
• Fine-tune, evaluate, and optimize LLMs using supervised fine-tuning and reinforcement learning techniques.
• Integrate AI/ML solutions with enterprise applications, APIs, and cloud platforms.
• Develop scalable and production-ready AI services using Python and modern backend frameworks.
• Create and manage vector databases, embeddings, semantic search, and knowledge retrieval systems.
• Ensure model performance, security, privacy, explainability, and responsible AI practices.
• Collaborate with cross-functional teams to understand business requirements and translate them into AI solutions.
• Monitor, troubleshoot, and continuously improve deployed AI models and services.

Required SkillsTechnical Skills

• Strong experience in Python programming.
• Hands-on experience with Generative AI and LLM frameworks such as LangChain, LlamaIndex, Semantic Kernel, or Haystack.
• Good understanding of Large Language Models, prompt engineering, embeddings, transformers, and fine-tuning.
• Experience with RAG architecture and vector databases such as Pinecone, Weaviate, Chroma, FAISS, or Milvus.
• Knowledge of OpenAI, Azure OpenAI, Google Vertex AI, AWS Bedrock, Anthropic, or Hugging Face.
• Experience with machine learning and deep learning frameworks such as PyTorch or TensorFlow.
• Knowledge of REST APIs, FastAPI, Flask, or Django.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with containerization and deployment tools such as Docker and Kubernetes.
• Knowledge of databases such as SQL, PostgreSQL, MongoDB, or NoSQL databases.
• Experience with Git, CI/CD pipelines, and MLOps practices.

• Experience in multi-agent AI systems and autonomous agents.
• Knowledge of model evaluation, observability, and monitoring tools.
• Experience with speech-to-text, text-to-speech, OCR, and multimodal AI solutions.
• Exposure to AI governance, ethical AI, and data privacy standards.
• Experience in building AI copilots for business applications.
• Familiarity with domain-specific use cases in healthcare, finance, retail, insurance, or telecom.

• Certifications in AWS, Azure, GCP, or Generative AI technologies.
• Experience working in Agile/Scrum environments.
• Contributions to open-source AI/ML projects.
• Experience with prompt testing, model benchmarking, and AI experimentation frameworks.

Example Use Cases

The candidate may work on:

• AI-powered customer support chatbot
• Intelligent document processing and summarization
• Internal enterprise knowledge assistant
• Automated email/content generation
• AI copilot for developers, HR, sales, or operations
• Semantic search and recommendation engines

Soft Skills

• Strong analytical and problem-solving skills
• Excellent communication and stakeholder management
• Ability to work independently and in a team environment
• Strong attention to detail and continuous learning mindset
• Ability to explain complex AI concepts to non-technical stakeholders

Pay: £450.00-£480.00 per day

Work Location: Hybrid remote in Leeds (West Yorkshire, Yorkshire and Humber Region)