Location
In office (Leeds)
Employment
Contractor
Confirmed on the employer's own hiring board on Oct 25, 2026. First seen by Alion on Feb 25, 2026.
Overview
Company
Impact
Profile match
Headquartered in London, United Kingdom, Yadimen Consulting is a specialized management and technology consulting practice focused on financial services transformation across Europe, the Middle East, and Africa (EMEA). The firm provides expert strategic advisory, program delivery, and specialized engineering services across critical areas such as regulatory compliance, operational resilience, core platform modernization, payments, lending, and digital customer experience. By combining senior industry practitioners with an AI-augmented intelligence layer, the company helps banks, financial institutions, and global enterprises navigate complex regulatory frameworks, upgrade legacy IT infrastructure, and accelerate secure digital transformation.
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
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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