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About the role
About Inveno Inveno is a VC backed, US headquartered startup building an AI operating system that runs supply chain operations inside Fortune 500 production systems deterministic decisioning, computer-use agents driving enterprise-grade software with no integration, and a data ontology for real-world physical operations. Our agents are in production today at some of the worlds largest companies, making operational decisions every shift where a wrong call is a missed truck, not a bad chat reply. What youll work on: outcome-based learning loops with proprietary models, multi-site scale across millions of transactions, and replanning under live operational data problems that dont have existing solutions. As part of a small team youll own a core layer outright the data ontology, the decision models, or the operator agents and your code will shape how companies operate in the physical world. The Team Our CTO and engineering team are based in Bangalore, while the co-founders and commercial team are based in the US. The founding team combines 15 years of warehouse and supply chain technology experience at companies including GreyOrange and Walmart, repeat founder experience from ventures scaled to millions of dollars in ARR, and deep enterprise GTM relationships across warehouse automation and logistics software. We are also bringing in a founding Data Science Lead who was the first hire for Amazons Supply Chain Data Science team in India, and went on to build and lead that team. In short, we understand how warehouses operate, how enterprise buyers make decisions, and how to build production grade software for complex physical operations. The Role Scientist in the team will work towards building the core models for system.Will also help develop a digital twin to replicate business processes that will help simulate the impact of optimization modelsBuild Agentic solutions to reduce the amount of effort for extending solutions to multiple customersWill build the ability to write enterprise code that can be directly deployed to productionWe expect engineers here to build what they own and own what they ship. That includes debugging across application, database, infrastructure, and distributed system boundaries, and being available for production support when needed.You may also use AI coding tools such as Codex, Claude, Gemini, or similar tools thoughtfully to move faster while maintaining quality. What We Are Looking For >5 years experience in building science models (forecasting, statistical, simulation or optimization)Ability to write clean and testable code in Python, Java or C#Hands on experience with solvers like Gurobi, Xpress or HexalyWorking understanding of data structures and algorithms. Able to identify the time complexity of algorithms to write to most efficient heuristics.Ability to read scientific literature and determine the right solution approach for our business problemsAbility to write basic sql code to build your own data layerAbility to dive deep into the business processes and find the right opportunity to optimize operationsGreat verbal and written communicationHigh ownership bar The Kind of Engineer Who Will Do Well Here You enjoy hard problems and messy systems.You think in first principles, not shortcuts.You can move between architecture diagrams, code reviews, logs, database queries, and debugger sessions without ego.You understand that quality is not only QAs job.You want to build software that enterprise customers trust when things cannot fail. Location Bangalore, India Employment Type Full time Compensation Compensation will be competitive and aligned with demonstrated competency for an early stage startup role in Bangalore. We expect the package to include fixed salary and potential equity participation, depending on experience, role level, and candidate fit. Final compensation will be discussed during the interview process. About Inveno Inveno is a VC backed, US headquartered startup building an AI operating system that runs supply chain operations inside Fortune 500 production systems deterministic decisioning, computer-use agents driving enterprise-grade software with no integration, and a data ontology for real-world physical operations. Our agents are in production today at some of the worlds largest companies, making operational decisions every shift where a wrong call is a missed truck, not a bad chat reply. What youll work on: outcome-based learning loops with proprietary models, multi-site scale across millions of transactions, and replanning under live operational data problems that dont have existing solutions. As part of a small team youll own a core layer outright the data ontology, the decision models, or the operator agents and your code will shape how companies operate in the physical world. The Team Our CTO and engineering team are based in Bangalore, while the co-founders and