Job Description

Key Responsibilities:

  • Design and implement Generative AI applications using LLMs, RAG (Retrieval-Augmented Generation), and Agentic AI frameworks.
  • Develop and fine-tune LLMs leveraging frameworks such as LangChain, Hugging Face Transformers, and LangGraph.
  • Build prompt engineering pipelines and ensure optimal model performance for specific business use cases.
  • Implement MLOps practices for model versioning, training automation, and continuous integration using MLflow, AWS SageMaker, or Azure ML.
  • Architect and optimize vector database integrations (e.g., FAISS, Pinecone, Chroma, Weaviate).
  • Work closely with data engineers and product teams to operationalize AI workflows.
  • Deploy, monitor, and optimize AI/ML models in production on AWS / Azure environments.
  • Ensure AI governance, security, and ethical compliance across all AI deployments.
  • Collaborate with cross-functional teams to evaluate new too...

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