Engineering Manager - Aftermarket, Cloud and Data Analytics

About the job

Key Responsibilities: Platform Leadership • Own and drive the development of the complete video telematics ecosystem, covering edge AI, video processing, cloud platform, and data insights. • Architect and oversee scalable and secure cloud infrastructure for video streaming, data storage, OTA updates, analytics, and alerting systems. • Define the data pipeline architecture for collecting, storing, analyzing, and visualizing video, sensor, and telematics data. Cross-functional Engineering Management • Lead and coordinate cross-functional teams: • Cloud/backend team for infrastructure, APIs, analytics dashboards, and system scalability. • AI/ML and CV teams for DMS/ADAS model deployment and real-time inference. • Hardware/Embedded teams for firmware integration, camera tuning, and SoC optimization. • Collaborate with product and business stakeholders to define the roadmap, features, and timelines. Data Analytics • Work closely with data scientists to build meaningful insights and reports from video and sensor data. • Drive implementation of real-time analytics, fleet safety scoring, and predictive insights using telematics data. Operational Responsibilities • Own product quality and system reliability across all components. • Support product rollout, monitoring, and updates in production. • Manage resources, mentor engineers, and build a high-performing development team. • Ensure adherence to industry standards for security, privacy (GDPR), and compliance (e.g., GSR, AIS-140). Pre-Requisites: • 7+ years of experience in software/product engineering, with 2+ years in a technical leadership or management role. • Deep understanding of cloud architecture, video pipelines, edge computing, and microservices. • Proficient in AWS/GCP/Azure, Docker/Kubernetes, serverless computing, and RESTful API design. • Solid grasp of AI/ML integration and computer vision workflows (model lifecycle, optimization, deployment). • Experience in data pipelines, SQL/NoSQL databases, and analytics tools (e.g., Redshift, Snowflake, Grafana, Superset).

Requirements

• cloud architecture
• video pipelines
• edge computing
• microservices

Preferred Technologies

• cloud architecture
• video pipelines
• edge computing
• microservices