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