

Gazelle Global
Senior AI Engineer
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior AI Engineer, a 6-month contract position with a pay rate of "£X per day", located in "Remote". Key skills include Python, Azure OpenAI Services, and multi-agent system design. Experience in retail AI solutions is preferred.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
July 14, 2026
🕒 - Duration
Unknown
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🏝️ - Location
Unknown
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
London Area, United Kingdom
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🧠 - Skills detailed
#Strategy #AI (Artificial Intelligence) #Microservices #Python #Cloud #Security #Azure #Deployment #"ETL (Extract #Transform #Load)" #Scala
Role description
The Role This role will have a significant impact on delivering innovative solutions for one of the leading retailers in the UK, driving digital transformation and enhancing customer experiences.
About the Role
You’ll work on projects that leverage cutting-edge technologies such as microservices, event-driven architectures, and cloud platforms, contributing to scalable, secure, and high-performing systems.
Responsibilities
• Design and develop agentic AI systems capable of multi-step reasoning, planning, and action execution
• Build scalable AI applications using Python as the core development language
• Develop and integrate solutions using Azure OpenAI Services, including prompt engineering, embeddings, and fine-tuning strategies
• Implement orchestration pipelines using Semantic Kernel and LangGraph for multi-agent workflows
• Integrate tools, APIs, and enterprise systems using MCP (Model Context Protocol) or similar frameworks
• Design memory, state management, and context-aware agent behaviors
• Optimize performance, cost, and latency of LLM-based solutions
• Collaborate with solution architects, product teams, and stakeholders to translate business use cases into AI solutions
• Ensure governance, security, and responsible AI practices are embedded into solutions
Required Skills
• Design agent architectures
• Define orchestration patterns
• Design tool strategy and integration approach
• Lead implementation of AI services
• Establish coding standards and best practices
• Guide evaluation and safety approaches
• Support production deployments and troubleshooting
Preferred Skills
• Design multi-agent solutions
• Design RAG architecture
• Implement complex orchestration workflows
• Build scalable AI microservices
• Define AI governance patterns
• Troubleshoot production AI solutions
Technologies
• Azure OpenAI
• Azure AI Foundry
• Semantic Kernel
• LangGraph
• MCP
• Azure AI Search
• Event-driven architectures
The Role This role will have a significant impact on delivering innovative solutions for one of the leading retailers in the UK, driving digital transformation and enhancing customer experiences.
About the Role
You’ll work on projects that leverage cutting-edge technologies such as microservices, event-driven architectures, and cloud platforms, contributing to scalable, secure, and high-performing systems.
Responsibilities
• Design and develop agentic AI systems capable of multi-step reasoning, planning, and action execution
• Build scalable AI applications using Python as the core development language
• Develop and integrate solutions using Azure OpenAI Services, including prompt engineering, embeddings, and fine-tuning strategies
• Implement orchestration pipelines using Semantic Kernel and LangGraph for multi-agent workflows
• Integrate tools, APIs, and enterprise systems using MCP (Model Context Protocol) or similar frameworks
• Design memory, state management, and context-aware agent behaviors
• Optimize performance, cost, and latency of LLM-based solutions
• Collaborate with solution architects, product teams, and stakeholders to translate business use cases into AI solutions
• Ensure governance, security, and responsible AI practices are embedded into solutions
Required Skills
• Design agent architectures
• Define orchestration patterns
• Design tool strategy and integration approach
• Lead implementation of AI services
• Establish coding standards and best practices
• Guide evaluation and safety approaches
• Support production deployments and troubleshooting
Preferred Skills
• Design multi-agent solutions
• Design RAG architecture
• Implement complex orchestration workflows
• Build scalable AI microservices
• Define AI governance patterns
• Troubleshoot production AI solutions
Technologies
• Azure OpenAI
• Azure AI Foundry
• Semantic Kernel
• LangGraph
• MCP
• Azure AI Search
• Event-driven architectures






