AI Platform Engineer
Posted Today by KBC Technologies Group
Negotiable
Undetermined
Undetermined
England, United Kingdom
Summary: The role of AI Platform Engineer involves leading the development of next-generation MCP server-based connectivity infrastructure on Microsoft Azure. Candidates must possess strong technical execution skills and deep experience in Azure AI ecosystems to deliver production-grade solutions rapidly. The position emphasizes AI integration, technical leadership, and system optimization within a high-priority, 3-month engagement.
Key Responsibilities:
- Design, develop, and manage MCP servers and gateway infrastructure
- Implement secure, scalable, and observable AI connectivity layers
- Apply policies, routing logic, and governance controls across MCP ecosystems
- Ensure seamless integration between AI tools, agents, and backend services
- Lead engineering efforts for integrating AI agents with applications and MCP servers
- Define and enforce architecture standards and best practices
- Collaborate with cross-functional teams to ensure alignment with Azure AI architecture
- Provide technical direction for AI connectivity and orchestration layers
- Identify and resolve performance bottlenecks in AI infrastructure
- Optimize Azure-based AI workloads for scalability and efficiency
- Ensure stability of end-to-end MCP and AI integration pipelines
- Improve observability, monitoring, and system diagnostics
Key Skills:
- Expert-level hands-on experience with Azure AI Foundry (Azure AI Studio)
- Strong understanding of Azure AI ecosystem and services
- Proven experience in designing and deploying MCP servers
- Strong background in system integration, APIs, and connectivity frameworks
- Experience in building AI agent-based architectures
- Strong proficiency in Python (mandatory)
- Experience in building production-grade backend systems
- Strong experience in Microsoft Azure
- Exposure to distributed systems and cloud-native architecture
- Excellent stakeholder communication and collaboration
- Ability to work in fast-paced, high-pressure environments
Salary (Rate): undetermined
City: undetermined
Country: United Kingdom
Working Arrangements: undetermined
IR35 Status: undetermined
Seniority Level: undetermined
Industry: IT
Role Overview We are seeking Hands-on Lead / Senior AI Engineers for a high-priority, 3-month engagement focused on building next-generation MCP (Model Context Protocol) server-based connectivity infrastructure on Microsoft Azure. The role requires strong technical execution skills, deep experience in Azure AI ecosystems , and the ability to deliver fast, production-grade solutions from day one .
Key Responsibilities
- MCP Infrastructure Development
- Design, develop, and manage MCP servers and gateway infrastructure
- Implement secure, scalable, and observable AI connectivity layers
- Apply policies, routing logic, and governance controls across MCP ecosystems
- Ensure seamless integration between AI tools, agents, and backend services
- AI Integration & Technical Leadership
- Lead engineering efforts for integrating AI agents with applications and MCP servers
- Define and enforce architecture standards and best practices
- Collaborate with cross-functional teams to ensure alignment with Azure AI architecture
- Provide technical direction for AI connectivity and orchestration layers
- System Optimization & Reliability
- Identify and resolve performance bottlenecks in AI infrastructure
- Optimize Azure-based AI workloads for scalability and efficiency
- Ensure stability of end-to-end MCP and AI integration pipelines
- Improve observability, monitoring, and system diagnostics
Required Skills & Experience
- Cloud AI Expertise
- Expert-level hands-on experience with Azure AI Foundry (Azure AI Studio)
- Strong understanding of Azure AI ecosystem and services
- MCP & Integration Engineering
- Proven experience in designing and deploying MCP servers
- Strong background in system integration, APIs, and connectivity frameworks
- Experience in building AI agent-based architectures
- Programming & Engineering Skills
- Strong proficiency in Python (mandatory)
- Experience in building production-grade backend systems
- Cloud Platform Experience
- Strong experience in Microsoft Azure
- Exposure to distributed systems and cloud-native architecture
- Soft Skills
- Excellent stakeholder communication and collaboration
- Ability to work in fast-paced, high-pressure environments