Gen AI Developer

Role & responsibilities

We are looking for a Generative AI Engineer with strong hands-on experience in LLMs, RAG, AI Agents, Python and Azure to build and deploy production-grade enterprise GenAI applications.

Key Responsibilities

• Develop Generative AI applications using LLMs, prompt engineering, RAG and AI Agents.
• Build RAG pipelines covering document ingestion, chunking, embeddings, vector search, retrieval, reranking and response generation.
• Develop AI agents and agentic workflows using tool/function calling and multi-step execution.
• Integrate enterprise systems using REST APIs, tools and MCP.
• Develop backend services and APIs using Python and C#/.NET.
• Work with Azure OpenAI, Azure AI Foundry and Azure AI Search.
• Implement LLM evaluation, monitoring, logging, guardrails and Responsible AI practices.
• Troubleshoot and optimize GenAI applications for accuracy, latency, reliability and cost.
• Follow Git, CI/CD and software engineering best practices.
• Collaborate with architects, developers, product owners and business teams.

Must-Have Skills

• 57 years of software development experience with hands-on Generative AI experience.
• Strong Python programming skills and experience building production APIs.
• Good understanding of C#/.NET.
• Strong knowledge of LLMs, prompt engineering, embeddings and context management.
• Hands-on experience building RAG applications.
• Understanding of Vector Databases, Vector Search and Hybrid Search.
• Experience developing AI Agents, tool calling and agentic workflows.
• Experience with LangChain, LangGraph, Microsoft Agent Framework or similar frameworks.
• Hands-on experience with Azure OpenAI.
• Experience with Azure AI Search and/or Azure AI Foundry.
• Strong understanding of REST APIs, microservices, Git and CI/CD.
• Experience deploying and supporting production-grade applications.
• Experience with MCP and MCP server/tool integration.
• Experience with multi-agent systems and agent orchestration.

Good to Have

• Azure Functions, Mongo DB and Blob Storage.
• Docker, Kubernetes/AKS, Terraform and Azure DevOps.
• Kafka / event-driven architecture.
• Experience with LLM evaluation, guardrails, and Responsible AI.
• Knowledge of AI security, prompt injection, and data protection.
• Experience with LLM observability, tracing, and performance optimization.

Core Technology Stack

GenAI: LLMs | RAG | Prompt Engineering | Embeddings | Vector Search | AI Agents | MCP

Frameworks: Microsoft Agent Framework | LangChain | LangGraph

Azure: Azure OpenAI | Azure AI Foundry | Azure AI Search | Functions | Cosmos DB | Blob Storage

Backend: Python | FastAPI | C#/.NET | REST APIs | Microservices

Engineering: Git | CI/CD | Docker | Kubernetes | Terraform | Azure DevOps

Preferred candidate profile