• 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
Skills Required
- Hands-on experience building solutions with LLMs, AI APIs, Copilot Studio, or agent frameworks
- Strong understanding of RAG architectures, vector databases, embeddings, and retrieval optimization
- Experience with Microsoft Azure AI services, cloud-native engineering, and secure deployment patterns
- Experience with agent engineering, including orchestration, lifecycle management, versioning, and drift detection
- Secure-by-design mindset, including authentication, authorization, data protection, and auditability
- Familiarity with DevOps, CI/CD, infrastructure as code, observability, and modern engineering pipelines
- Ability to debug hallucinations, variability, reliability issues, and other unexpected AI behavior
- Strong documentation skills and ability to produce reusable code assets and templates
What We Do
Yadimen Consulting is a technology consulting firm focused on financial-services organizations. It delivers technology implementation and strategic consulting services, drawing on expertise in data engineering, fraud strategy, data science, enterprise platforms, and product implementation. The company operates across the US, UK, Nordic countries, and Western Europe, helping clients address sector-specific technology challenges and opportunities through tailored solutions for financial institutions and regulated businesses.
