Manager - IoT and Private Networks

About The CompanyTata Communications Redefines Connectivity with Innovation and IntelligenceDriving the next level of intelligence powered by Cloud, Mobility, Internet of Things, Collaboration, Security, Media services and Network services, we at Tata Communications are envisaging a New World of CommunicationsJob DescriptionResponsible for architecting and deploying AI first products and solutions. This role focuses on designing and implementing multi-agent systems, data pipelines, model development and optimisation and MLOps. Driving implementation strategies aligned to product requirements and engineering standards.ResponsibilitiesUnderstand IoT-specific requirements including data ingestion from edge devices, sensors and cameras and user-facing application features.Lead technical discussions with cross-functional teams (e.g., hardware, cloud, analytics) to evaluate feasibility, define specifications, and assess performance and scalability for IoT solutions.Develop and optimize machine learning, deep learning models to meet industry-specific needs, focusing on improving model accuracy, efficiency, and scalability.Design, development, and deployment of end-to-end machine learning pipelines, ensuring smooth data ingestion, preprocessing, model training, validation, and deployment to production.Implement MLOPS best practices to streamline model deployment, monitoring, and maintenance. Facilitate prioritization of features related to device data processing, predictive maintenance, anomaly detection, and real-time user interfaces.Desired Skill Sets Strong experience architecting and delivering Software applications combining real-time data, Edge and Cloud-native full stack platforms. Hands-on expertise with Large Language Models, RAG (Retrieval-Augmented Generation), Prompt Engineering, AI Agents and open source GenAI ecosystem. Expertise in Computer Vision and techniques such as Object Detection, Object Tracking, Pose Estimation, OCR etc. Thorough understanding of DNN (Deep Neural Networks), Reinforcement Learning, Time Series Forecasting. Predictive Analytics, Text Classification and YOLO framework. Deep understanding of software/application lifecycle management for connected device platforms Experience working in Agile setups and DevOps pipelines with tools like Docker, Kubernetes, Jenkins, Git etc.