Artificial Intelligence Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for an Artificial Intelligence Engineer in London, UK, on a contract (Inside IR35) with a pay rate of "unknown". Key skills include Generative AI, MLOps, Python, and cloud platforms. Experience in architecting GenAI chatbots and Agile frameworks is preferred.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
-
🗓️ - Date discovered
September 23, 2025
🕒 - Project duration
Unknown
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🏝️ - Location type
On-site
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📄 - Contract type
Inside IR35
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🔒 - Security clearance
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Consulting #SageMaker #Security #Monitoring #Kubernetes #AI (Artificial Intelligence) #Network Security #AWS (Amazon Web Services) #Databases #Deployment #Azure #Automation #Docker #TensorFlow #Langchain #ML (Machine Learning) #Hugging Face #Agile #Python #GCP (Google Cloud Platform) #Libraries #Cloud #Data Science #PyTorch #Sentiment Analysis #Observability #MLflow
Role description
Role: Lead AI Engineer
Location: London, UK
Type: Contract (Inside IR35)
Job Description:
• Proven expertise in Generative AI, Agentic AI, traditional Machine Learning, and automation technologies.
• Deep understanding of:
• Prompt Engineering
• Retrieval-Augmented Generation (RAG) pipelines
• Supervised and Unsupervised Model Tuning
• MLOps/LLMOps pipelines
• AI observability tools and practices
• Hands-on experience designing and deploying enterprise-grade RAG-based solutions using LLMs (e.g., OpenAI, Hugging Face, LLaMA) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Strong experience in architecting and scaling GenAI-powered chatbots.
• Proficiency in Agentic AI, including practical experience with frameworks such as LangGraph, AutoGen, and CrewAI, and orchestration tooling (e.g., MCP servers) on at least one major hyperscaler platform.
• Solid understanding of Responsible AI principles and ethical AI deployment practices.
• Ability to translate business problems into analytical and AI-driven solutions through strong collaboration with business, data science, and engineering teams.
• Excellent communication, stakeholder management, and consulting skills, with the ability to influence and align cross-functional teams.
• Track record of driving productivity improvements and cost optimization through AI initiatives.
Technical Skills:
• Python with ML/AI libraries (e.g., PyTorch, TensorFlow)
• Prompt Engineering tools and techniques
• GenAI & Agentic AI frameworks (e.g., Langchain, LangSmith, LangFuse)
• Cloud platforms: Azure (AI Foundry), AWS (Bedrock/SageMaker), GCP (Vertex AI)
• MLOps/LLMOps tools: MLflow, Kubeflow, Docker, Kubernetes
Preferred Qualifications
• Experience delivering AI/ML projects within Agile development frameworks
• Hands-on work with Model Feedback Analysis, topic modeling, and sentiment analysis
• Familiarity with AgentOps and OpenTelemetry for monitoring and managing agent-based systems
• Understanding of network security concepts, network telemetry, and analytics
Role: Lead AI Engineer
Location: London, UK
Type: Contract (Inside IR35)
Job Description:
• Proven expertise in Generative AI, Agentic AI, traditional Machine Learning, and automation technologies.
• Deep understanding of:
• Prompt Engineering
• Retrieval-Augmented Generation (RAG) pipelines
• Supervised and Unsupervised Model Tuning
• MLOps/LLMOps pipelines
• AI observability tools and practices
• Hands-on experience designing and deploying enterprise-grade RAG-based solutions using LLMs (e.g., OpenAI, Hugging Face, LLaMA) and vector databases (e.g., Pinecone, Weaviate, FAISS).
• Strong experience in architecting and scaling GenAI-powered chatbots.
• Proficiency in Agentic AI, including practical experience with frameworks such as LangGraph, AutoGen, and CrewAI, and orchestration tooling (e.g., MCP servers) on at least one major hyperscaler platform.
• Solid understanding of Responsible AI principles and ethical AI deployment practices.
• Ability to translate business problems into analytical and AI-driven solutions through strong collaboration with business, data science, and engineering teams.
• Excellent communication, stakeholder management, and consulting skills, with the ability to influence and align cross-functional teams.
• Track record of driving productivity improvements and cost optimization through AI initiatives.
Technical Skills:
• Python with ML/AI libraries (e.g., PyTorch, TensorFlow)
• Prompt Engineering tools and techniques
• GenAI & Agentic AI frameworks (e.g., Langchain, LangSmith, LangFuse)
• Cloud platforms: Azure (AI Foundry), AWS (Bedrock/SageMaker), GCP (Vertex AI)
• MLOps/LLMOps tools: MLflow, Kubeflow, Docker, Kubernetes
Preferred Qualifications
• Experience delivering AI/ML projects within Agile development frameworks
• Hands-on work with Model Feedback Analysis, topic modeling, and sentiment analysis
• Familiarity with AgentOps and OpenTelemetry for monitoring and managing agent-based systems
• Understanding of network security concepts, network telemetry, and analytics
