Engineering Manager - Cloud Architecture

Description :

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 :

o Cloud/backend team for infrastructure, APIs, analytics dashboards, and system scalability.

o AI/ML and CV teams for DMS/ADAS model deployment and real-time inference.

o 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).

Requirements :

Must-Have :

- Bachelors or Masters in Computer Science, Electrical Engineering, or related field.

- 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).

Good-to-Have :

- Experience with camera hardware (MIPI, ISP tuning), compression codecs (H.264/H.265),
and event-based recording.

- Familiarity with telematics protocols (CAN, MQTT) and geospatial analytics.

- Working knowledge of data privacy regulations (GDPR, CCPA)