Description

You design and implement AI solutions, building and refining retrieval-augmented generation (RAG) pipelines for enterprise applications.

Responsibilities

• Design and implement RAG pipelines utilizing hybrid search, vector, keyword, semantic ranking, and metadata enrichment.
• Apply chunking strategies (fixed size, recursive, semantic, agentic) to optimize document segmentation for retrieval and embedding.
• Fine-tune and evaluate Large Language Models (LLMs) like GPT, LLaMA, and Ollama for tasks such as QA, summarization, NER, and sentiment analysis.
• Build and integrate multi-agentic systems into enterprise applications using Azure OpenAI, Cognitive Search, Azure Functions, and Power Automate.
• Ensure model reliability, performance, and ethical compliance across all deployments.

Required Skills

• 8 to 12 years of experience as a Fullstack Developer, with 2 to 4 years specifically in generative AI or RAG systems.
• Proficiency in Azure AI Studio and Azure Cognitive Services.
• Expertise in Python and .NET.
• Strong knowledge of VectorDBs (e.g., Pinecone, FAISS), chunking techniques, and embedding strategies.
• Experience with MLOps tools, MLflow, Docker, and CI/CD pipelines.
• Expertise in prompt engineering and model evaluation.
• Mandatory familiarity with Agentic Systems and Multi-Agent Orchestration.
• Good knowledge of the SDLC Lifecycle.

Key Skills

Education

Any Gradute