Gen AI Engineer

Educational Requirements

• Bachelor of Engineering,Bachelor Of Technology (Integrated)

Service Line 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.

Additional Responsibilities

• 2-5 years of experience in AI/ML, Generative AI, LLM Engineering, or MLOps.
• Strong understanding of LLM lifecycle management and production deployment.
• Experience building enterprise AI assistants, chatbots, search, or knowledge management solutions.
• Excellent problem-solving and analytical skills.
• Effective communication and collaboration abilities.

Technical and Professional Requirements

• Docker
• Kubernetes
• CI/CD Pipelines
• MLflow
• Terraform
• MLOps Platforms
• Agentic AI Frameworks (CrewAI, AutoGen, LangGraph)
• Knowledge Graphs
• NLP Machine Learning Fundamentals

Preferred Skills

• Technology->AI-Generative AI->Artificial Intelligence - BASIC
• Technology->AI-Data science->Machine Learning
• Technology->AI-Generative AI->Generative AI for Data Analytics