Sr Product Manager, Forecasting Tools, Demand Planning & Workforce Intelligence

Amazon Development Centre (India) Private Limited is a technology-focused corporate entity associated with Amazon that operates research, engineering, and product development activities in India. Functioning as one of Amazon’s India-based development centers, the company is oriented around software engineering, systems design, data science, and product delivery to support Amazon’s consumer retail platform, cloud services, device software, advertising technologies, logistics and supply chain systems, and other global Amazon businesses. The centre serves as a multi-disciplinary engineering and innovation hub where teams of software engineers, product managers, data scientists, research scientists, program managers, and operations specialists collaborate to design, build, test, and launch services and features used by millions of customers and partners worldwide. Core business activities at the Amazon Development Centre include end-to-end software product development, platform and infrastructure engineering, machine learning and artificial intelligence research and implementation, and large-scale data engineering. Engineering teams work on backend services, front-end product experiences, scalable distributed systems, and cloud-native architectures that underpin Amazon’s e-commerce marketplace and customer-facing services. The centre also contributes to Amazon Web Services (AWS) projects, including developer tooling, monitoring and observability, database and storage solutions, and services that enable enterprise and consumer customers to leverage cloud capabilities. Product and service areas that receive direct engineering investment from Amazon Development Centre teams typically include search and discovery algorithms, personalized recommendations, fraud detection and payments systems, catalog and inventory management, seller and vendor platforms, fulfillment optimization and route planning, and advertising platforms. In addition to retail-facing technology, the development centre often engages in consumer device software and services (including digital assistant and voice technologies), multimedia and digital content delivery optimizations, and tooling that supports Amazon’s logistics network and marketplace participants. The centre places significant emphasis on applied machine learning, natural language processing, and data science to improve customer experiences and operational efficiency. Teams develop and deploy models for personalization, demand forecasting, pricing and promotions, language understanding for voice assistants, image recognition for product listings, and anomaly detection for security and fraud prevention. These capabilities are integrated into product features across Amazon’s ecosystem, supporting both customer engagement and internal operational decision-making. A sizeable portion of the activity within the development centre is devoted to platform engineering and developer productivity: creating internal services, APIs, and platforms that enable Amazon’s global engineering workforce to move quickly and safely. This includes building observability tooling, automated deployment pipelines, performance optimization frameworks, and security and compliance automation. Such infrastructure work is intended to increase engineering velocity while maintaining reliability and data protection standards appropriate for large-scale, customer-facing systems. The Amazon Development Centre also supports research and experimentation. Cross-functional research groups and labs collaborate on proof-of-concept work, prototype new product ideas, and partner with academic institutions and local technology communities. Projects originating at the development centre may progress from pilot programs to full-scale production services that are rolled out globally. The centre’s contributions span both incremental product improvements and longer-term innovation investments, aligning with Amazon’s broader engineering and business priorities. Teams at the centre are typically organized by product area or technical capability, such as core retail services, AWS integrations, device and Alexa software, advertising technology, supply chain engineering, and machine learning infrastructure. Engineers operate within agile, iterative development cycles and leverage a combination of open-source software and proprietary systems. Collaboration across global Amazon offices is a routine part of operations; the India-based centre works closely with counterparts in North America, Europe, and other regions to integrate features and ensure global scalability and compliance. Beyond product engineering, the entity supports enterprise functions tied to technology operations, including technical program management, site reliability engineering (SRE), security engineering, and technical recruiting. The centre often participates in talent development initiatives, internships, and partnerships with universities to foster local engineering expertise and to attract specialists in software, data science, and cloud computing. Public-facing activities associated with Amazon development centres in India include recruitment drives, technical events, hackathons, participation in local developer ecosystems, and publication of research or engineering blog posts that describe engineering challenges and solutions. These interactions reflect an orientation toward both building commercial products and contributing to the broader technology community. While specific legal and corporate details (such as registered office addresses and formal entity identifiers) are maintained in official corporate registries and filings, the principal, verifiable character of Amazon Development Centre (India) Private Limited is as a technology research and development hub under the broader Amazon corporate umbrella. Its role is to deliver engineering, research, and technical services that enhance Amazon’s consumer offerings, cloud services, marketplace operations, and device platforms, leveraging software engineering, large-scale systems design, and data-driven approaches to solve complex problems at scale.