Key Responsibilities
- Design and implement AI and Generative AI solutions.
- Build RAG, Agentic AI, and LLM-based applications.
- Develop ML models for prediction, recommendation, and analytics.
- Manage AI platforms on AWS, GCP, and Azure.
- Implement MLOps, CI/CD, model monitoring, and deployment pipelines.
- Lead and mentor AI/ML engineering teams.
- Collaborate with stakeholders to drive AI transformation projects.
Required Skills
- Generative AI & LLMs (GPT-4, Claude, LLaMA, Gemini)
- RAG / Agentic AI
- LangChain, LangGraph, LlamaIndex
- Python, SQL, PyTorch, TensorFlow
- AWS, GCP, Azure
- Kubernetes, Docker, MLflow, Kubeflow
- Vector Databases (FAISS, ChromaDB)
Preferred Certifications
- AWS Machine Learning Specialty
- Google Professional ML Engineer
- Microsoft Azure Data Scientist Associate
Education
Bachelor’s or Master’s Degree in Computer Science, AI, Data Science, or related field.