Description

Build and operate production-grade AI solutions focused on Retrieval-Augmented Generation and agent orchestration.

This role is on-site.

Responsibilities

• Design and operate RAG services using Azure AI/Search, covering chunking, embeddings, re-ranking, and citation display.
• Deploy Model Context Protocol (MCP) tools to integrate security scanners, inventory, approvals, and Azure DevOps/GitHub.
• Build agentic AI solutions using AutoGen, CrewAI, or Agno for secure tool-calling and multi-agent workflow automation.
• Develop multi-turn, retrieval-grounded chatbots, managing prompts, guardrails, logging, and telemetry.
• Ship code via CI/CD on Azure DevOps, implementing tests, red-teaming for prompt injection, and documenting runbooks.

Required Skills

• 4+ years total software development experience, with 2+ years applied to LLM/GenAI.
• Strong Python skills and hands-on experience with Azure OpenAI and Azure AI/Search (vector/hybrid search).
• Practical experience with agent frameworks (AutoGen, CrewAI, Agno) and MCP/tool-use patterns.
• Proven Azure PaaS experience: Azure Functions or Web Apps, APIM, Key Vault, and Event Hub.
• Experience implementing observability using App Insights and Log Analytics/KQL.
• Familiarity with Entra ID/RBAC and secure API design principles.
• Experience with CI/CD pipelines using Azure DevOps.
• Ability to evaluate and fine-tune open-source models (PEFT/LoRA) balancing quality and cost.
• A security-first mindset covering content safety and prompt-injection defenses.

Preferred Skills

• Experience with RAG evaluation frameworks (e.g., Ragas) or custom golden sets.
• Familiarity with Cosmos DB.

Key Skills

Education

Any Gradute