Job Description
Responsibilities: Design and implement end-to-end AI solutions using LLMs (e.g., GPT-based or open-source models) Build and optimize Retrieval-Augmented Generation (RAG) pipelines for enterprise use cases Develop agentic AI systems capable of autonomous reasoning, planning, and task execution Architect and deliver goal-based AI platforms with full-stack capabilities (frontend, backend, APIs) Integrate AI models into scalable applications using microservices architecture Deploy, monitor, and scale AI workloads on AWS (e.g., EC2, S3, Lambda, SageMaker) Apply NLP techniques for text processing, semantic search, classification, and summarization Work with vector databases (e.g., Pinecone, FAISS, OpenSearch) Ensure model performance, reliability, and security in production environments Collaborate with cross-functional teams including product, data, and DevOps Requirements 2+ years of experience in AI Engineering, Data Science, Machine Learning, or related fields. Hands-on experience in Generative AI, Hands on experience in Large Language Models (LLMs) Hands on experience in Natural Language Processing (NLP) Hands on experience in Python Hands on experience in MLOps Hands-on experience with cloud platforms such as Azure and AWS. Experience building full-stack applications using JavaScript, React, APIs, and SQL databases. Familiarity with Agile methodologies, JIRA. Experience leading teams and managing stakeholders. Strong analytical, problem-solving, and communication skills.
