Key Responsibilities :

- Design, develop, and deploy Generative AI and LLM-based applications on Azure.

- Build enterprise-grade Retrieval-Augmented Generation (RAG) solutions.

- Develop end-to-end RAG pipelines including document ingestion, chunking, embeddings, retrieval, reranking, and response generation.

- Work with Azure AI Foundry to develop, evaluate, and deploy AI applications.

- Integrate LLMs and Azure OpenAI with enterprise applications and data sources.

- Implement prompt engineering and optimize prompts for accuracy and reliability.

- Work with vector databases/vector search technologies for semantic retrieval.

- Evaluate LLM and RAG applications for quality, relevance, latency, and cost.

- Develop APIs and services to integrate AI capabilities into business applications.

- Implement monitoring, security, governance, and responsible AI practices.

- Collaborate with data engineers, software engineers, architects, and business teams to deliver production-ready AI solutions.

Required Skills :

- 8 to 15 years of experience in software engineering, AI/ML engineering, or related fields.

- Strong hands-on experience with Azure AI Foundry.

- Strong experience with Generative AI and LLMs.

- Hands-on experience designing and implementing RAG architectures.

- Experience with Azure OpenAI / LLM APIs.

- Strong Python programming skills.

- Experience with embeddings, vector search/vector databases, and semantic retrieval.

- Good understanding of prompt engineering and LLM evaluation.

- Experience building and deploying production-grade AI applications.

- Strong understanding of Azure cloud services and AI architecture.