Job
Description
Job DescriptionWe are seeking an experienced AI/ML Engineer with expertise in Generative AI, Machine Learning, and AWS Cloud to design, develop, deploy, and optimize AI-driven solutions. The ideal candidate should have hands-on experience in building scalable ML models, implementing GenAI use cases using LLMs, and deploying AI applications on AWS.
Roles & Responsibilities(Generative AI, ML,AWS)
Design/deploy ML pipelines and LLM-powered agents (RAG, Agentic AI) using AWS Bedrock, SageMaker, LangGraph
Develop, train, and productionize ML models (churn, recommendation, forecasting) with MLOps practices
Build RAG architectures, integrate LLM APIs, prompt engineering, and responsible AI guardrails
Strong Python (Scikit-learn, TensorFlow, PyTorch); hands-on SageMaker; vector DBs (FAISS, Pinecone, OpenSearch)
Must-have: Python, LangGraph/LangChain, Bedrock/OpenAI integration | Nice-to-have: LLM fine-tuning, LangSmith/W&B, AWS ML Specialty
Technical RequirementStrong proficiency in Python and AI/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.Hands-on experience with Generative AI and Large Language Models (LLMs).Experience with OpenAI, Claude, Gemini, Llama, or similar foundation models.Strong understanding of Prompt Engineering, RAG, Embeddings, and Vector Databases.Experience with LangChain, LangGraph, LlamaIndex, or similar frameworks.Hands-on experience with AWS Services such as:SageMakerBedrockLambdaEC2S3GlueAPI GatewayCloudWatchStrong SQL and data processing skills.Experience with REST APIs and microservices architecture.Knowledge of Git, CI/CD, and Agile methodologies. Educational RequirementMCA,MSc,MTech,BTech Preferred SkillsTechnology->AI-Generative AI->Generative AI for Data Analytics,Technology->AI-Data science->Machine Learning Service LineData & Analytics Unit
