·   Have degree or master’s degree in the field of AI / ML and data science with proven ability to design and develop models

· 8+ years of experience in software development, data science, and ML, with at least 3+ years in AI engineering roles.

·   Proven experience in the end-to-end ML lifecycle: data wrangling, model development, deployment, and monitoring.

· Strong programming skills in Python with Solid knowledge of AI/ML, including LLMs and data science libraries like pandas, scikit-learn, TensorFlow/PyTorch, etc.

·    Experience with LLM orchestration frameworks like Langchain, LangGraph, vLLM, LMDeploy.

·     Strong knowledge in NoSQL databases (any experience in Graph database is desirable)

·      Experience with MLOps tools: MLflow, Airflow, Kubeflow, or similar.

·  Familiarity with either of cloud platforms (GCP, AWS) for AI Solutioning and ML deployment.

·  Knowledge of data science techniques including supervised/unsupervised learning, NLP, time series, etc.

·     Experience with CI/CD pipelines and containerization (Docker, Kubernetes).

·     Strong understanding of AI governance, model risk management, and regulatory equirements in AI.

·        Ability to communicate technical concepts to non-technical stakeholders.