Description

You will design and implement RAG pipelines using hybrid search, vector, keyword, semantic ranking, and metadata enrichment.

You will apply chunking strategies including fixed size, recursive, semantic, and agentic methods to optimize document segmentation for retrieval and embedding.

Responsibilities

• Design and implement RAG pipelines with hybrid search and semantic ranking.
• Apply chunking strategies to optimize document segmentation for retrieval.
• Collaborate with stakeholders to translate business needs into scalable AI solutions.
• Ensure model reliability, performance, and ethical compliance across deployments.

Required Skills

• 5 to 7 years of experience as a Fullstack Developer.
• 2 to 4 years in generative AI or RAG systems.
• Proficiency in Python.
• Experience with chunking techniques and embedding strategies.
• Familiarity with MLOps tools, MLflow, Docker, and CI/CD pipelines.
• Experience with prompt engineering and model evaluation.

Preferred Skills

• Familiarity with Agentic Systems and Multi-Agent Orchestration.

Key Skills

Education

Bachelor's degree