Microsoft AI CoPilot Developer

Yadimen Consulting Limited; Leeds; On-site; GBP 65,000 - 95,000; Full time

Job summary

Yadimen Consulting Limited is seeking a skilled AI Engineer to design, develop, and maintain Copilot agents, plugins, and LLM workflows. You will build scalable components, integrate with enterprise systems, and implement secure AI practices within a modern cloud-native stack.

The role focuses on RAG architectures, vector databases, embeddings, and retrieval optimization, with emphasis on observability, governance, and reusable code assets. Collaborative, cross-functional work is expected.

Qualifications

• Hands-on experience building solutions with LLMs, AIAPIs, Copilot Studio, or agent frameworks.
• Strong understanding of RAG architectures, vector databases, embeddings, and retrieval optimisation.
• Experience with Microsoft Azure AI services, cloud-native engineering, and secure deployment patterns.
• Experience with agent engineering: orchestration, lifecycle management, versioning, drift detection.
• Familiarity with DevOps, CI/CD, IaC, observability, and modern engineering pipelines.
• Ability to debug unexpected AI behaviour - hallucinations, variability, reliability issues.
• Strong documentation skills and ability to produce reusable code assets and templates.

Responsibilities

• Design, develop, and maintain Copilot agents, plugins, connectors, and LLM workflows in Copilot Studio
• Build scalable components: prompt orchestration, retrieval layers, Power Automate flows, model interfaces, validation pipelines
• Develop and optimise RAG components - embeddings, vector queries, metadata strategies for accuracy and reliability
• Integrate AI agents with enterprise systems via Microsoft Graph, APIs, and Power Platform connectors
• Implement secure-by-design and responsible AI practices: guardrails, controls, monitoring, auditability
• Build observability: logging, telemetry, and LLM monitoring for quality and incident triage
• Create reusable assets - prompt libraries, agent templates, connectors, test harnesses, and documentation
• Conduct rapid prototyping to validate feasibility, model behaviour, UX, and performance
• Enable pro-/low-/no-code teams to adopt AI safely - support the satellite model across business functions

Skills

LLM development

Copilot Studio

Agent frameworks

RAG architectures

Vector databases

Azure AI services

DevOps / CI-CD

Tools

Copilot Studio

Microsoft Graph

Power Platform connectors

Job description

Leeds, United Kingdom | Posted on 02/25/2026

Responsibilities

• Design, develop, and maintain Copilot agents, plugins, connectors, and LLM workflows in Copilot Studio
• Build scalable components: prompt orchestration, retrieval layers, Power Automate flows, model interfaces, validation pipelines
• Develop and optimise RAG components - embeddings, vector queries, metadata strategies for accuracy and reliability
• Integrate AI agents with enterprise systems via Microsoft Graph, APIs, and Power Platform connectors
• Implement secure-by-design and responsible AI practices: guardrails, controls, monitoring, auditability
• Build observability: logging, telemetry, and LLM monitoring for quality and incident triage
• Create reusable assets - prompt libraries, agent templates, connectors, test harnesses, and documentation
• Conduct rapid prototyping to validate feasibility, model behaviour, UX, and performance
• Enable pro-/low-/no-code teams to adopt AI safely - support the satellite model across business functions

Requirements

• Hands-on experience building solutions with LLMs, AIAPIs, Copilot Studio, or agent frameworks
• Strong understanding of RAG architectures, vector databases, embeddings, and retrieval optimisation
• Experience with Microsoft Azure AI services, cloud-native engineering, and secure deployment patterns
• Experience with agent engineering: orchestration, lifecycle management, versioning, drift detection
• Familiarity with DevOps, CI/CD, IaC, observability, and modern engineering pipelines
• Ability to debug unexpected AI behaviour - hallucinations, variability, reliability issues
• Strong documentation skills and ability to produce reusable code assets and templates