AI Engineer

Key Responsibilities AI & Machine Learning Development

• Design, develop, and deploy AI/ML models for business use cases.
• Build and optimize machine learning pipelines from data preparation to model deployment.
• Develop predictive, classification, recommendation, and NLP solutions.
• Fine-tune and evaluate foundation models and LLMs.

Generative AI Solutions

• Design and implement Generative AI applications using LLMs.
• Develop Retrieval-Augmented Generation (RAG) solutions.
• Create prompt engineering frameworks and reusable AI workflows.
• Integrate AI copilots, chatbots, and virtual assistants into enterprise platforms.
• Implement AI governance, monitoring, and responsible AI practices.

Data Engineering & Integration

• Collaborate with Data Engineers and Data Scientists to prepare training datasets.
• Develop APIs and microservices for AI model consumption.
• Integrate AI services with enterprise systems and cloud platforms.

Model Deployment & Monitoring

• Deploy AI solutions using MLOps best practices.
• Monitor model performance, accuracy, drift, and reliability.
• Ensure scalability, security, and compliance requirements are met.