Job Description: Staff Software Engineer

Role Overview We are seeking an experienced technology professional (8–10 years) with an engineering background (B.Tech / Masters) and strong expertise in Edge Computing, Edge AI, IoT, and Cloud integration. This role combines hands‑on technical leadership with strategic oversight, focusing on deploying AI/ML models at the edge, enabling anomaly detection and predictive maintenance, and integrating IoT devices with cloud platforms for scalable analytics.

Key Responsibilities

Design and deploy Edge AI solutions for anomaly detection and predictive maintenance.Optimize and run AI/ML models at the edge on constrained devices for real‑time insights.Manage model lifecycle — training, validation, deployment, monitoring, and retraining.Continuously fine‑tune models to adapt to evolving data patterns and maintain accuracy.Validate third‑party connectors, gateways, and converters to ensure reliability in edge deployments.Integrate IoT devices with edge/cloud platforms (Azure, AWS, GCP) for secure pipelines and scalable analytics.Provide technical leadership and mentor teams on best practices in Edge AI and IoT.

Qualifications

8–10 years of experience in IoT, Edge Computing, or Cloud‑based analytics roles.Engineering degree (B.Tech / Masters) in Computer Science, Electronics, Electrical, or related fields.Proven expertise with Edge Computing platforms (Azure IoT Edge, AWS Greengrass, NVIDIA Jetson, etc.).Strong knowledge of AI/ML frameworks (TensorFlow Lite, PyTorch Mobile, ONNX Runtime) and deployment on constrained devices.Hands‑on experience with IoT protocols (MQTT, CoAP, Modbus, OPC UA) and device integration.Practical exposure to cloud services for IoT and analytics (Azure IoT Hub, AWS IoT Core, Google Cloud IoT).Demonstrated success in predictive maintenance and anomaly detection projects.

Preferred Attributes

Experience with containerization/orchestration for edge workloads (Docker, Kubernetes at the edge).Knowledge of hybrid cloud‑edge architectures for scalable IoT deployments.Strong communication skills to bridge technical detail with executive‑level clarity.Collaborative mindset with proven ability to lead teams and drive adoption of edge/cloud solutions.