IOT Cloud Engineer

We are seeking an experienced IIoT Engineer with strong expertise in AWS and .NET development to architect and deploy scalable, secure IIoT solutions that integrate with IIoT ecosystems. The ideal candidate will be capable of deploying these solutions both in cloud and on-premises environments. This role involves designing cloud-native and containerized applications, implementing infrastructure as code, building microservices using .NET, and designing Unified Namespace (UNS) models for industrial data contextualization. Exposure to Kubernetes and Docker.

· Strong hands-on experience in architecting and building IoT Solution using AWS SiteWise, AWS IoT Core, AWS Greengrass, AWS IoT Rules Engine, Kinesis, Lambda, Greengrass, SNS, Dynamo DB, EC2, S3 etc.

· Experience in building functionalities/logic using Lambda Functions

· Experience in creating and deploying .Net based Micro service-based architectures, testing and deployment automation

· Utilize Docker and Kubernetes for containerized application deployment across edge and cloud
Experience in deployment in Cloud PaaS and Kubernetes based deployment on bare metal

· Exposure to AWS IoT Analytics, Amazon Quicksight, Amazon SageMaker, Amazon Bedrock etc.

· Strong understanding of core architectural concepts including distributed computing, scalability, availability and performance

· Experience in Requirement Understanding, Design and Development of IoT Solutions

· Experience in Cloud Computing, SOA, and Web Technologies

· Experience in frameworks for Middleware development such as Service Bus, Message Queues etc.

· Experience on building Generative AI based solutions using AWS technologies

· Understanding of any other leading IoT platforms such as Azure is an added advantage

· Develop and manage CI/CD pipelines using tools like Jenkins, GitHub Actions, or GitLab CI/CD.

· Design and maintain UNS models to enable contextualized data flow across OT/IT systems.

· Familiarity with edge frameworks such as Greengrass, HighByte Intelligence Hub, Litmus Edge, or Ignition by Inductive Automation.

· Enable real-time data ingestion from connected devices and optimize performance across platforms.

· Ensure compliance with industry standards and best practices for security, reliability, and scalability.

· Collaborate with cross-functional teams including edge engineers, software developers, and data scientists to deliver intelligent edge-to-cloud solutions.

· Support deployments in manufacturing environments, integrating with PLCs, SCADA, MES, and Historian systems.

· Solid understanding of OPC-UA and MQTT protocols.

· Exposure to digital twin platforms like TwinMaker, nVidia Omniverse, industrial cybersecurity, and data governance frameworks would be beneficial