Overview

Design, develop, deploy, and maintain Generative AI applications using LLMs. Build and operationalize LLM pipelines across development, testing, and production environments. Implement LLMOps best practices for model deployment, monitoring, evaluation, governance, and lifecycle management.

Responsibilities

• Design, develop, deploy, and maintain Generative AI applications using LLMs.
• Build and operationalize LLM pipelines across development, testing, and production environments.
• Implement LLMOps best practices for model deployment, monitoring, evaluation, governance, and lifecycle management.
• Develop Retrieval-Augmented Generation (RAG) solutions using enterprise knowledge repositories.
• Integrate LLMs with APIs, databases, business applications, and cloud services.
• Monitor model performance, latency, cost optimization, hallucinations, and model drift.
• Create automated CI/CD pipelines for AI model deployment and versioning.
• Collaborate with Data Scientists, ML Engineers, and Cloud Teams to deliver scalable AI solutions.
• Ensure security, compliance, observability, and responsible AI practices across GenAI platforms.

Qualifications

• 2-5 years of experience in AI/ML, Generative AI, LLM Engineering, or MLOps.
• Robust understanding of LLM lifecycle management and production deployment.
• Experience building enterprise AI assistants, chatbots, search, or knowledge management solutions.

Nice to have

• Excellent problem-solving and analytical skills.
• Effective communication and collaboration abilities.