Design, develop, and deploy AI/ML solutions to solve business problems across operations, manufacturing, supply chain, and enterprise applications. | Build production-grade applications using Large Language Models (LLMs), Retrieval Augmented Generation (RAG), AI agents, and modern AI frameworks. | Develop and optimize machine learning, computer vision, NLP, and predictive analytics models based on business requirements. | Collaborate with Product Managers and business stakeholders to understand problems, identify AI opportunities, and translate them into scalable solutions. | Prepare, clean, and engineer datasets for training, evaluation, and production deployment. | Build APIs and AI services that integrate seamlessly with web applications, mobile applications, ERPs, and enterprise systems. | Evaluate emerging AI models, frameworks, and technologies to continuously improve solution quality and business impact. | Monitor model performance, accuracy, latency, and reliability, and continuously improve deployed AI systems. | Document AI architectures, experiments, and deployment pipelines while following engineering best practices. | Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field (B.Tech./B.E. preferred). | 1–3 years of experience developing AI/ML applications in production environments. | Strong hands-on experience with Python (mandatory). | Experience with machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, or XGBoost. | Experience building applications using modern LLMs (OpenAI, Claude, Gemini, Llama, etc.). | Hands-on experience with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks. | Strong SQL skills and experience working with structured and unstructured datasets. | Experience building REST APIs using FastAPI, Flask, or similar frameworks. | Familiarity with cloud platforms such as AWS, Azure, or GCP. | Python | Machine Learning | Deep Learning | Generative AI | Large Language Models (LLMs) | Retrieval Augmented Generation (RAG) | AI Agents | Prompt Engineering | NLP | Computer Vision | Vector Databases | SQL | Git | Docker | API Development | Experience deploying AI solutions into production environments. | Experience with OCR, document intelligence, or multimodal AI systems. | Experience with computer vision applications using OpenCV, YOLO, or related frameworks. | Familiarity with MLOps tools such as MLflow, Airflow, Kubeflow, or similar platforms. | Experience working with manufacturing, logistics, industrial automation, or supply chain datasets. | Exposure to IoT, robotics, or sensor data is an added advantage. | Strong analytical and problem-solving skills with a first-principles approach. | Curiosity to experiment with emerging AI technologies while maintaining engineering discipline. | Ability to independently own AI projects from idea to production deployment. | Strong communication skills and the ability to explain AI concepts to non-technical stakeholders. | Passion for building practical AI solutions that create measurable business impact rather than proof-of-concepts.