GEN AI

Job Summary

Key Responsibilities

• Design and develop AI/ML solutions for large-scale enterprise applications.
• Build and optimize distributed data processing pipelines using Apache Spark and Databricks.
• Develop and deploy Generative AI applications using LLMs such as GPT, Llama, Claude, and Mistral.
• Implement Retrieval-Augmented Generation (RAG) frameworks and vector databases.
• Utilize High-Performance Computing (HPC) environments to accelerate AI model training and inference.
• Fine-tune foundation models and optimize model performance for production workloads.
• Develop scalable data engineering and MLOps pipelines.
• Collaborate with Data Scientists, Data Engineers, and Business Stakeholders to deliver AI-driven solutions.
• Monitor, troubleshoot, and optimize AI applications in production environments.
  

Required SkillsAI & Generative AI

• Generative AI, Large Language Models (LLMs)
• Prompt Engineering
• RAG (Retrieval-Augmented Generation)
• LangChain, LlamaIndex
• Fine-tuning and Model Evaluation
• AI Agents and Multi-Agent Systems
  

Data Engineering & Big Data

• Apache Spark (PySpark)
• Databricks
• Delta Lake
• Data Modeling and ETL/ELT Pipelines
• SQL and NoSQL Databases
  

Programming

• Python
• SQL
• REST APIs
  

High-Performance Computing

• HPC Clusters
• Distributed Computing
• Parallel Processing
• GPU Computing (NVIDIA CUDA preferred)
  

Cloud & MLOps

• Azure / AWS / GCP
• MLflow
• Docker
• Kubernetes
• CI/CD Pipelines
• Git