AI Engineer

• Design, build, test, and deploy Python based AI agents capable of executing complex, multi-step workflows across enterprise systems.

• Develop and integrate MCP servers to enable secure, standardized, and context aware interactions between AI agents, enterprise APIs, databases, internal tools, and knowledge repositories.

• Build LLM powered applications using agentic frameworks, tool use orchestration, prompt engineering, and workflow automation patterns.

• Develop custom Retrieval Augmented Generation using embeddings, vector databases, metadata filtering, document chunking, and semantic search.

• Integrate AI services with enterprise applications using Python, C# , .NET, REST APIs, GraphQL, and SQL based data sources .

• Implement secure tool calling patterns, role-based access controls, audit logging, human in the loop approvals, and traceability mechanisms.

• Build reusable AI components, agent tools, prompt templates, evaluation scripts, and orchestration workflows.

• Collaborate with AI Architects and Data Modelers to ensure AI solutions use accurate, governed, and explainable data.

• Support deployment, monitoring, troubleshooting, and performance tuning of AI applications in cloud or enterprise environments.

• Create clear technical documentation covering architecture, prompts, data flows, APIs, MCP interfaces, dependencies, and operational procedures.

• Conduct knowledge transfer sessions with S&P Global internal engineering teams.