About the role

What you’ll do

• Design, develop, and deploy an Agentic AI platform for AI-driven customer solutions
• Build and integrate scalable data pipelines, AI services, and models across enterprise environments
• Implement data preprocessing, embedding generation, and RAG pipelines using LLMs and multimodal models
• Integrate AI/data solutions across cloud and on-premise environments with Docker and Kubernetes
• Implement MLOps, LLMOps, and DataOps practices including CI/CD, monitoring, and lifecycle management
• Support platform performance, security, and governance

What you’ll need

• Bachelor's or Master's degree in Computer Science, Data Engineering, AI, or related field
• 5+ years of experience in AI/data engineering and implementation roles
• 2+ years building end-to-end Generative AI and data-driven solutions including RAG pipelines with LLMs and multimodal models
• Experience with data processing frameworks, pipeline development, and vector databases such as Milvus, PGVector, or Pinecone
• Strong Python programming skills with Pandas/PySpark and API development, plus cloud/on-prem integration using Docker and Kubernetes
• Solid understanding of data governance, security, compliance, and MLOps/LLMOps/DataOps practices

Original job description