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Azure AI Video Indexer is part of the Edge AI group, dedicated to bringing AI capabilities to customers who need to manage workloads on-premises using Azure Arc technologies. It delivers intelligent, real-time video insights directly at the source of data. Running on Azure Local or Arc-connected Kubernetes infrastructure, Video Indexer ensures data privacy while analyzing live video streams for scenarios such as safety monitoring, anomaly detection, and retail operations. Customers can stream RTSP camera feeds to the edge deployment and view both the live video and AI-driven insights in real time. With conversational interaction and natural language customization, Video Indexer at the edge combines operational agility with a privacy-first architecture, making it ideal for industries that require immediate, compliant insights without sending sensitive data to the cloud.
Job Responsibility:
Design, develop, and maintain media encoding pipelines and live streaming workflows for both cloud and on-premises environments
Build infrastructure, tools, and real-time monitoring systems that ensure reliable live video delivery and operational visibility
Write code that integrates with Azure resources and extensions, leveraging modern technology stacks and methodologies
Break down complex problems, create clear execution plans, and take full ownership of your code from development through production
Collaborate within a multi-disciplinary team
Automate quality control and alerting mechanisms to rapidly detect and resolve streaming issues, ensuring a seamless experience for customers streaming camera feeds and viewing live video alongside AI-driven insights
Requirements:
5+ years of experience with SW development using C#, Java, Python or similar language
Practical experience with AI-based or agentic development tools (e.g., GitHub CopilotAgent, Cursor, Claude Code, Cline)
Highly Familiar with distribution formats such as MPEG-TS, HLS, MPEG-DASH, and CMAF, including segmenting and packaging for live and on-demand delivery
Solid understanding of end-to-end streaming systems design: ingest (e.g., RTSP), processing/analytics pipelines, packaging/origin, CDN delivery, player behavior, and operational observability (metrics, logging, alerting)
B.Sc. in Computer Science or equivalent
Ability to automate quality control and alerting for streaming workflows to detect and resolve streaming issues rapidly
Familiarity with video transport protocols such as RTSP, RTP, RTMP, SRT and related streaming technologies
WebRTC experience for interactive streaming scenarios
Proven experience with real-time or streaming data processing (e.g. Kafka or similar)
Proven ability to lead complex tasks in unfamiliar domains and deliver them to production
Experience developing and operating code in cloud environments (Azure / AWS / GCP)
Experience with Docker, Kubernetes, and modern CI/CD practices
Team player with proven communication skills
A proactive, ownership-driven approach with the ability to lead complex projects end-to-end
Proven problem-solving and coding skills with a passion for elegant architecture
Demonstrated ability to think creatively and being resilient to change
Hands-on experience with DeepStream (by NVIDIA) for building and operating real-time video analytics and streaming pipelines