Description

1. Must have hands on expertise in LLMs, NLP, RAG, Agentic AI, and enterprise AI automation.
2. Strong experience with GPT 4, Claude, LLaMA, Mistral, BERT, T5, Hugging Face, OpenAI APIs.
3. Ability to design and deploy RAG solutions using vector databases like FAISS, Pinecone, Weaviate, OpenSearch, or Elasticsearch.
4. Must have built AI chatbots, copilots, virtual assistants, and document intelligence solutions for enterprise use cases.
5. Experience in fine tuning and optimization using LoRA, QLoRA, PEFT, instruction tuning, prompt engineering, and model quantization.
6. Strong MLOps and production deployment experience using MLflow, Kubeflow, Airflow, Docker, Kubernetes, Azure ML, AWS SageMaker, or GCP Vertex AI.
7. Should be capable of building real time AI/ML pipelines using Spark, Kafka, Databricks, Snowflake, Python, and FastAPI.
8. Must be able to convert business problems into AI use cases across fraud, compliance, customer support, knowledge search, document processing, and automation.
9. Should have strong stakeholder facing ability to work with executives, product owners, architects, and delivery teams to drive GenAI adoption responsibly

Key Skills

Education

Bachelor's degree