Agent AI Developer

Key Responsibilities

• Architect, develop, test, deploy, and support AI agents using Microsoft Azure, Azure OpenAI, Microsoft Foundry, and suitable agent-development frameworks.
• Implement agentic workflows including planning, function/tool calling, multi-agent coordination, approval gates, and human-in-the-loop review.
• Build and maintain MCP clients and servers to connect agents securely to enterprise tools, services, APIs, and governed data sources.
• Integrate agents with enterprise systems, relational or document databases, REST APIs, Microsoft services, and business applications.
• Implement identity and access management, secrets handling, data privacy controls, responsible AI guardrails, and safeguards against prompt injection and unsafe tool execution.
• Develop maintainable services and reusable components in Python and/or C#; establish code quality, testing, versioning, deployment, and documentation standards.
• Evaluate agent quality, tool reliability, latency, cost, observability, and operational behavior; diagnose and remediate production issues.
• Provide technical leadership, review designs and code, mentor engineers where applicable, and collaborate with stakeholders to deliver measurable business outcomes.

Mandatory Technical Skills

• Microsoft Azure and Azure OpenAI: hands-on solution development, deployment, and service integration.
• LLM-powered agents: demonstrable implementation of agentic workflows, tool/function calling, and orchestration beyond simple chat or prompt prototypes.
• Microsoft Foundry: working knowledge of its capabilities and relevant agent development patterns/frameworks.
• Programming: strong proficiency in Python and/or C# with sound API and software engineering practices.
• MCP and integrations: practical understanding of MCP clients/servers, tool connectivity, API orchestration, and enterprise integration.
• Retrieval and search: hands-on vector search, embeddings, and Azure AI Search or equivalent technology.
• Security: identity management, authentication/authorization, least-privilege access, secrets management, and AI-specific security considerations.
• Engineering effectiveness: troubleshooting, debugging, design communication, collaboration, and technical documentation.

Preferred / Value-Adding Skills

• Microsoft Agent Framework; Microsoft Fabric; Microsoft Graph; and SharePoint integration.
• Azure Functions, Logic Apps, API Management, and Azure Service Bus.
• Agent evaluation, LLM observability/tracing, quality measurement, and prompt-injection mitigation.
• LangGraph or similar agent orchestration frameworks.
• Proven delivery of enterprise AI solutions at scale, including operational monitoring and cost/performance optimization.

Experience & Qualifications

• 8+ years of experience in software engineering, cloud development, or enterprise integration.
• 3+ years of relevant AI/ML or Generative AI experience preferred.
• Demonstrated production delivery of AI agents beyond proof-of-concept or demonstration stages.
• Ability to independently drive technical implementation, make sound architecture decisions, and work effectively across teams.
• Bachelors degree in Computer Science, Engineering, Information Technology, or a related discipline preferred.