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AI Engineer

Caterpillar

Chennai Tamil NaduFull TimeMidH-1B sponsor company
Sign in to applyVerified
Location
Chennai Tamil Nadu
Employment
Full Time
Work model
On-Site
Level
Mid
H-1B history
106 approvals (FY2023)
Posted

About this role

Career Area: Technology, Digital and Data Job Description: Your Work Shapes the World at Caterpillar Inc. When you join Caterpillar, you're joining a global team who cares not just about the work we do – but also about each other.  We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here – we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it. Caterpillar IT is at the forefront of enabling Caterpillar’s digital transformation, delivering technology solutions that support our global business, manufacturing operations, products, and customers. We leverage data, cloud technologies, advanced analytics, AI, and modern software engineering to build secure, scalable, and innovative solutions that improve operational efficiency and help Caterpillar build a better, more sustainable world.   Build the Digital Backbone of Modern Manufacturing We’re assembling a dynamic team to develop and scale our Manufacturing & Supply Digital Platform—a next-generation software framework that transforms how manufacturing and supply operations connect, collaborate, and optimize.   This platform is not an ERP system. It’s a purpose-built digital layer that integrates data, processes, and resources across the entire manufacturing lifecycle—from design and engineering to production and distribution.   This initiative is powered by NVIDIA technologies, including the Omniverse platform and AI computing capabilities, enabling immersive digital twins, accelerated simulation, and intelligent automation. You’ll be part of a team that’s not just building software—but shaping the future of how manufacturing works through AI-driven, collaborative, and scalable digital solutions.   As part of this initiative, you’ll contribute to: System Integration: Seamlessly connecting diverse manufacturing and supply systems, data sources, and workflows into a unified digital ecosystem. Data-Driven Decision Making: Harnessing real-time data collection, analysis, and visualization to deliver actionable insights and operational intelligence. Automation & Optimization: Driving efficiency through intelligent scheduling, AI Agents, predictive maintenance, and quality control—without replacing core transactional systems. Enhanced Collaboration: Enabling transparent communication and coordination across teams, functions, and geographies.   If you're passionate about digital platforms, industrial innovation, and working with cutting-edge technologies—this is your opportunity to make a meaningful impact.

Key Responsibilities

Build, integrate, and optimize AI Assistants and agent-based solutions capable of retrieving information, executing workflows, and supporting business processes through natural language interactions. Develop and maintain integrations with enterprise data sources, APIs, knowledge bases, document repositories, and business applications to enable accurate and context-aware AI experiences. Implement prompt engineering, grounding, retrieval, memory management, and agent orchestration techniques to improve response quality, reliability, and user experience. Develop document ingestion, metadata extraction, chunking, indexing, and knowledge management pipelines to support enterprise search and AI Assistant capabilities. Evaluate, test, and optimize AI solutions using techniques such as prompt tuning, model selection, caching, reranking, and retrieval optimization to improve accuracy, latency, and cost efficiency. Collaborate with product, engineering, and domain teams to define requirements, translate business needs into AI capabilities, and deliver production-ready solutions. Implement observability, monitoring, evaluation, and feedback mechanisms to measure AI Assistant performance, identify issues, and drive continuous

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