Engineering Manager

Engineering Manager (ADAS)

About the Role We are seeking a seasoned

Engineering Manager

to lead the development of our end-to-end

Video Telematics and Cloud Analytics Platform . This role demands a strong technical leader with experience across

embedded systems ,

AI / ML ,

computer vision ,

cloud infrastructure , and

data analytics . You will be responsible for driving technical execution across multidisciplinary teams — overseeing everything from edge-based video analytics to cloud-hosted dashboards and insights. 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). Requirements : Must-Have : Bachelor’s or Master’s 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

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 : Prior work on

automotive ,

fleet , or

video telematics

solutions. 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).