AI Engineer

Job Description:

• Design, build, and deploy AI agents solving customer and business problems
• Create agents that deliver independent value and contribute insights to a broader intelligence ecosystem
• Translate product requirements and use cases into scalable, production-ready solutions
• Build and operate MCP servers providing secure access to tools, systems, and enterprise data
• Define and implement tool interfaces, authentication mechanisms, and resource access patterns
• Integrate agents with Dynamics 365, Microsoft Graph, Dataverse, ServiceNow, Contact Centre and Customer Experience platforms, and internal and third-party APIs
• Define memory, context, and decision-making patterns
• Implement retrieval, reasoning, and tool-use strategies
• Design safety guardrails for enterprise agent operation
• Develop adapters, event-processing capabilities, and integration layers
• Enable agents to share insights and consume intelligence from interconnected solutions
• Contribute technical expertise, customer insights, and market observations to the Agent Factory roadmap and backlog
• Work with Product, Engineering, QA, and AI leadership to meet security, performance, governance, and business-value standards
• Identify customer challenges, emerging AI opportunities, and market trends
• Support and maintain company information security standards

Requirements:

• Strong software engineering experience using C# and .NET
• Hands-on experience with Azure Functions, Azure App Service, Azure OpenAI Service, and Azure AI Foundry / AI Studio
• Experience integrating Dynamics 365, Dataverse, Microsoft Graph, and Power Platform
• Knowledge of Microsoft Entra ID, Managed Identities, and Azure Key Vault
• Practical experience building or consuming MCP servers
• Knowledge of Semantic Kernel, AutoGen, and Microsoft AI SDKs
• Experience with function and tool calling, RAG, vector databases, and context and memory management
• Ability to design clear, reliable, and secure agent interactions
• Strong API integration experience, including REST APIs, webhooks, and event-driven architectures
• Experience with cloud-native deployment, CI/CD pipelines, and infrastructure-as-code
• Understanding of performance, latency, reliability, and cost considerations for LLMs in production
• Commitment to software quality, testing, and continuous improvement
• Ability to work closely with QA teams on agent evaluation, testing, and quality assurance
• Pragmatic approach to taking ideas from concept to production
• Passion for applying AI to real-world business challenges
• Ability to work independently and collaborate with cross-functional teams
• Systems-thinking approach to platforms and architectures
• Security-conscious approach to reliable enterprise-grade solutions
• Nice to have: multi-agent architectures, agent-to-agent communication, enterprise or regulated-environment AI delivery, LLM observability/monitoring/tracing/evaluation, and Contact Centre/Customer Experience/workflow automation platforms
• All employees must adhere to information security policies, protect company and customer data, use systems securely, report incidents, complete mandatory security and data protection training, and handle confidential information securely

Benefits:

• Cutting-edge Microsoft AI technologies
• Opportunity to contribute directly to innovative agentic solutions
• Opportunity to help shape the future of enterprise AI
• Opportunity to build scalable AI capabilities delivering measurable customer value