Capgemini
Lead AWS IoT & Edge Deployment Specialist
Client is seeking an experienced AWS IoT and Edge Deployment Specialist to support the buildout of our smart manufacturing platform. This role is critical to the implementation of our future production environment, which integrates on-premises industrial equipment with AWS cloud and edge services. The ideal candidate has deep knowledge of the AWS IoT Greengrass ecosystem, industrial device integration, security best practices, and how telemetry data supports machine learning workflows using SageMaker.
Key Responsibilities
Lead the deployment and configuration of AWS IoT Greengrass and related edge services on industrial hardware
Design and implement secure data collection pipelines from factory devices (e.g., OPC-UA, Modbus) using IoT SiteWise, Greengrass components, and custom connectors
Support OTA (over-the-air) updates, configuration management, and remote debugging strategies
Design end-to-end observability and logging for edge and cloud-connected assets using CloudWatch, CloudTrail, and custom metrics
Ensure edge and cloud interactions meet security and compliance best practices (IAM roles, device certificates, encryption, auditability)
Collaborate with ML and data teams to enable edge-to-cloud telemetry flow for model training in SageMaker and inference deployment to edge
Help define and apply standards for data formats, labeling, versioning, and metadata tagging from edge sensors
Support validation and field testing efforts during deployment cycles across diverse factory environments
Contribute to documentation and runbooks to support maintainability and scalability of the edge-cloud architecture
Required Qualifications
3+ years of experience with AWS IoT services (Greengrass, IoT Core, SiteWise, IoT Jobs, IoT Device Defender)
Strong understanding of industrial protocols (OPC-UA, MQTT) and device integration patterns
Working knowledge of AWS security best practices for IoT, including certificates, policy management, and secure OTA
Experience building data collection or telemetry pipelines for downstream ML use cases (e.g., predictive maintenance, anomaly detection)
Familiarity with AWS services such as S3, Timestream, SageMaker, and CloudWatch
Excellent communication and documentation skills, with ability to work across DevOps, ML, and plant engineering teams
Nis to Have
AWS Certified Solutions Architect or AWS Certified Machine Learning – Specialty
Familiarity with Docker, container orchestration on edge (via Greengrass), and OTA pipelines
Experience with manufacturing compliance standards
Knowledge of data governance and lifecycle management for sensor data
Understanding of cloud-to-edge feedback loops (e.g., inference triggers, alerts, autonomous control actions)
Life at Capgemini Engineering Capgemini Engineering is a world leader in engineering and R&D services, combining broad industry knowledge with cutting-edge technologies to support Intelligent Industry. It employs engineers and scientists across 30+ countries and serves multiple sectors, including digital and software convergence with AI, cloud, and data capabilities.
Disclaimer Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. Capgemini is committed to providing reasonable accommodations during the recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. This description is not a contract and may be changed at any time.
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Key Responsibilities
Lead the deployment and configuration of AWS IoT Greengrass and related edge services on industrial hardware
Design and implement secure data collection pipelines from factory devices (e.g., OPC-UA, Modbus) using IoT SiteWise, Greengrass components, and custom connectors
Support OTA (over-the-air) updates, configuration management, and remote debugging strategies
Design end-to-end observability and logging for edge and cloud-connected assets using CloudWatch, CloudTrail, and custom metrics
Ensure edge and cloud interactions meet security and compliance best practices (IAM roles, device certificates, encryption, auditability)
Collaborate with ML and data teams to enable edge-to-cloud telemetry flow for model training in SageMaker and inference deployment to edge
Help define and apply standards for data formats, labeling, versioning, and metadata tagging from edge sensors
Support validation and field testing efforts during deployment cycles across diverse factory environments
Contribute to documentation and runbooks to support maintainability and scalability of the edge-cloud architecture
Required Qualifications
3+ years of experience with AWS IoT services (Greengrass, IoT Core, SiteWise, IoT Jobs, IoT Device Defender)
Strong understanding of industrial protocols (OPC-UA, MQTT) and device integration patterns
Working knowledge of AWS security best practices for IoT, including certificates, policy management, and secure OTA
Experience building data collection or telemetry pipelines for downstream ML use cases (e.g., predictive maintenance, anomaly detection)
Familiarity with AWS services such as S3, Timestream, SageMaker, and CloudWatch
Excellent communication and documentation skills, with ability to work across DevOps, ML, and plant engineering teams
Nis to Have
AWS Certified Solutions Architect or AWS Certified Machine Learning – Specialty
Familiarity with Docker, container orchestration on edge (via Greengrass), and OTA pipelines
Experience with manufacturing compliance standards
Knowledge of data governance and lifecycle management for sensor data
Understanding of cloud-to-edge feedback loops (e.g., inference triggers, alerts, autonomous control actions)
Life at Capgemini Engineering Capgemini Engineering is a world leader in engineering and R&D services, combining broad industry knowledge with cutting-edge technologies to support Intelligent Industry. It employs engineers and scientists across 30+ countries and serves multiple sectors, including digital and software convergence with AI, cloud, and data capabilities.
Disclaimer Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law. Capgemini is committed to providing reasonable accommodations during the recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact. This description is not a contract and may be changed at any time.
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