AI Product Engineer

This is a fully remote position, open to applicants in South Africa.

📋 Description

• Create, develop, and implement AI agents that address genuine customer and business challenges.

• Convert product specifications and use cases into scalable, production-ready solutions.

• Construct and manage Model Context Protocol (MCP) servers that provide secure access to tools, systems, and enterprise data.

• Establish and execute tool interfaces, authentication protocols, and resource access strategies.

• Integrate agents with Microsoft Dynamics 365, Microsoft Graph, Dataverse, ServiceNow, customer experience platforms, and both internal and third-party APIs.

• Design memory, context, decision-making, retrieval, reasoning strategies, tool-use protocols, and safety measures.

• Develop adapters, event-processing functionalities, and integration layers.

• Empower agents to exchange insights and utilize intelligence across interconnected solutions.

• Provide technical expertise, customer insights, and market observations to inform the Agent Factory roadmap and backlog.

• Collaborate with Product, Engineering, QA, and AI leadership teams.

• Adhere to enterprise standards for security, performance, governance, testing, and quality assurance.

• Maintain information security standards, safeguard company and customer data, use systems securely, report incidents, complete necessary training, and manage confidential information safely.

⛳️ Requirements

• Extensive software engineering experience with C# and .NET.

• Practical experience with Azure Functions, Azure App Service, Azure OpenAI Service, and Azure AI Foundry / AI Studio.

• Familiarity with integrating Dynamics 365, Dataverse, Microsoft Graph, and Power Platform.

• Understanding of Azure security and identity services, including Microsoft Entra ID, Managed Identities, and Azure Key Vault.

• Hands-on experience in building or utilizing MCP servers.

• Knowledge of Semantic Kernel, AutoGen, or Microsoft AI SDKs.

• Experience with function and tool invocation, Retrieval-Augmented Generation (RAG), vector databases, and context and memory management.

• Capability to design clear, dependable, and secure agent interactions.

• Strong experience in API integration with REST APIs, webhooks, and event-driven architectures.

• Experience in cloud-native deployment, CI/CD pipelines, and infrastructure-as-code.

• Awareness of LLM performance, latency, reliability, and cost factors in production environments.

• Dedication to software quality, testing, and ongoing improvement.

• Ability to collaborate with QA teams on agent evaluation, testing, and quality assurance.

• Capacity to work independently while collaborating with cross-functional teams.

• Security-focused approach to developing reliable enterprise-grade solutions.

• Nice-to-have: Experience with multi-agent architectures, AI solutions in regulated environments, LLM observability/monitoring/tracing/evaluation, and contact center or enterprise workflow automation platforms.

🏝️ Benefits

• Chance to influence the future of AI within a fast-paced product organization.

• Work with state-of-the-art Microsoft AI technologies.

• Make direct contributions to innovative agentic solutions.

• Play an essential role in developing scalable AI capabilities that provide measurable value to customers.