Job Description
WHAT YOU’LL DO
• 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
RequirementsMUST-HAVES
• Hands-on experience building solutions with LLMs, AI APIs, 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
• Secure-by-design mindset — authentication, authorisation, data protection, auditability
• 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
Requirements
MUST-HAVES • Hands-on experience building solutions with LLMs, AI APIs, 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 • Secure-by-design mindset — authentication, authorisation, data protection, auditability • 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
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