Responsibilities
- Design and build large-scale distributed systems for ingesting, processing, and indexing multimedia content from various global content providers.
- Architect and implement microservices on Kubernetes clusters that handle millions of daily requests with sub-second latency.
- Develop indexing pipelines to extract audio, video, and metadata features from multimedia content using signal processing and machine learning.
- Integrate agentic AI and large language model capabilities to improve development workflows and automate service operations like recovery.
- Build and operate multi-step agents that perform production tasks, including detecting service regressions, bisecting commits, proposing fixes, and generating code for team review.
- Develop internal tooling, skills, harnesses, and services to enhance engineering team efficiency and effectiveness.
- Achieve 95% work output using AI while maintaining clear quality standards.
- Optimize system performance for throughput, latency, and cost efficiency across multi-region cloud deployments.
- Design and implement monitoring, alerting, and observability solutions using tools like Prometheus, Grafana, the ELK stack, and distributed tracing.
- Lead technical design reviews and mentor engineers on distributed systems best practices, code quality, and architectural patterns.
- Participate in an on-call rotation to ensure system reliability and rapid incident response for production services.
- Drive continuous improvement initiatives, including performance optimization, cost reduction, and technical debt reduction.
