Senior AI Engineer with Azure, REMOTE WROCŁAW

• Strong background in Software Engineering, AI Engineering, or a related technical discipline.
• Proven hands-on experience delivering production-grade Agentic AI and LLM-powered solutions.
• Demonstrated experience designing, building, and deploying multi-agent AI systems in enterprise environments.
• Strong expertise in agent orchestration frameworks such as Azure AI Foundry Agent Service, Semantic Kernel, AutoGen, LangGraph, or similar.
• Experience building AI solutions using Azure OpenAI Service and/or Anthropic Claude models.
• Strong understanding of agent coordination, state management, context propagation, routing, handoffs, and failure handling.
• Hands-on experience developing MCP-based solutions and natural language interfaces for enterprise data.
• Strong experience with Azure services including Azure OpenAI, Azure AI Foundry, Azure Functions, Service Bus, API Management, and App Services.
• Experience integrating AI solutions with Microsoft Fabric lakehouses, warehouses, and data pipelines.
• Knowledge of event-driven architectures, asynchronous processing, and message-based workflows.
• Experience implementing secure and governed AI solutions, including RBAC, VNet integration, private endpoints, and enterprise compliance standards.
• Strong Python programming skills.
• Experience with CI/CD pipelines using Azure DevOps and/or GitHub Actions.
• Ability to work independently in complex and evolving business environments.
• Experience collaborating with architecture, security, and governance teams.

Nice to have:

• Experience with Copilot Studio agents or Microsoft 365 Copilot extensions.
• Experience integrating AI solutions with DealCloud, Salesforce, or similar CRM platforms.
• Experience with BuytheSell or other research and sales workflow platforms.
• Background in financial services, research, deal management, or relationship management domains.
• Experience implementing AI-driven scoring, targeting, engagement, or workflow automation solutions.
• Knowledge of Microsoft Purview for governance, compliance, and data lineage.
• Experience with Azure Monitor, Application Insights, or similar observability platforms.
• Understanding of Responsible AI, AI governance frameworks, and guardrail implementation.
• Experience with TypeScript.
• Experienced in using AI tools in day-to-day workflow

We are looking for a Senior AI Engineer to design, build, and deploy enterprise-grade multi-agent AI solutions on Microsoft Azure. The role focuses on developing structured, production-ready AI workflows that support research, sales, relationship management, and CRM automation processes.

Ability to maintain a minimum of four hours of daily overlap with London business hours (09:00–18:00 GMT/BST) and willingness to travel to London periodically for key project milestones and workshops.

Tech stack:

• Microsoft Azure & Microsoft Fabric
• Azure AI Foundry & Azure OpenAI Service
• Python
• AI Agent Frameworks (Semantic Kernel, AutoGen, LangGraph)
• MCP (Model Context Protocol)
• Azure DevOps / GitHub Actions
• Monitoring & Observability (Azure Monitor, Application Insights)
• Third-party integrations (DealCloud, BuytheSell)

,[Design and implement production-grade multi-agent AI systems supporting business workflows., Build and orchestrate agent interactions using Azure AI Foundry, Semantic Kernel, AutoGen, LangGraph, or equivalent frameworks., Develop deterministic, auditable, and observable AI workflows with proper state management., Implement agent routing, handoffs, context propagation, and failure recovery mechanisms., Design and develop MCP-based solutions and natural language interfaces over enterprise data., Build AI-accessible tools and MCP server components exposing business capabilities and data sources., Integrate AI solutions with Microsoft Fabric lakehouses, warehouses, APIs, and data pipelines., Develop integrations with DealCloud, BuytheSell, and other enterprise systems., Implement secure and governed access patterns, including RBAC and enterprise security controls., Build event-driven AI services using Azure Functions, Service Bus, and API Management., Establish monitoring, observability, audit trails, and AI governance controls., Define deployment, versioning, rollback, and lifecycle management standards for AI agents., Collaborate with architecture, security, and compliance teams to ensure alignment with enterprise requirements., Produce technical documentation, reusable architectures, and knowledge transfer materials., Drive end-to-end delivery from solution design through production deployment and handover.] Requirements: AI, Agentic AI, LLM, Azure AI Foundry Agent Service, Semantic Kernel, AutoGen, LangGraph, Azure OpenAI Service , Anthropic Claude models, Microsoft Fabric lakehouses, Warehouse, Data pipelines, event-driven architectures, asynchronous processing, AI Solutions, RBAC, VNet integration, Python, CI/CD Pipelines, Azure DevOps, GitHub Actions, Copilot Studio, MS 365 Copilot extensions, CRM, BuytheSell, Financial services, Research, Deal management, Microsoft Purview, Azure Monitor, Application Insights, TypeScript