Task Description: •    Master’s or Bachelor’s in Computer Science, Data Science, AI, or related field.

•    5+ years of experience in AI/ML engineering or equivalent senior-level capacity.

•    Strong expertise in Python, PyTorch, TensorFlow, Scikit learn.

•    Proven experience building and deploying LLM based applications.

•    Hands on experience with RAG architectures and vector databases.

•    Deep understanding of NLP, embeddings, generative AI, transformer models.

•    Strong knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow).

•    Experience with cloud platforms like Azure or GCP.

•    Experience with explainability, fairness testing, and responsible-AI tools.

•    Strong systems thinking and architectural design skills

•    Experience in agent frameworks (LangChain, LlamaIndex, Semantic Kernel).

MLOps, CI/CD & Productionization

•    Develop automated training, deployment, monitoring, and retraining pipelines.

•    Manage model versioning, model registry, feature stores, and drift detection pipelines.

•    Ensure high reliability, observability, and operational robustness of AI systems in production.

•    Architect end to end AI systems including data pipelines, model training, vector search, and high performance inference.

•    Lead design of LLM applications, agent-based systems, RAG workflows, and enterprise-grade AI automation.