Conviva is the experience analytics platform for AI agents, apps, and streaming. Conviva pioneered quality of experience measurement for streaming video and has supported live digital experiences across 20 Super Bowls, 10 Olympic Games, and five FIFA World Cup tournaments. With full-census, real-time, stateful analytics, Conviva shows what consumers actually experience, not just whether systems are running, and connects that experience to revenue, retention, and risk.
We are looking for an early-career engineer with deep foundations in distributed systems, AI/ML, or mathematics to join our Beijing engineering team. You will work on Conviva’s real-time analytics platform under direct mentorship from our China R&D leadership, and grow quickly into larger technical ownership.
Join us at the frontier of the agent analytics revolution, where we are defining the future of AI-native platforms. This is a rare opportunity to join a team that prioritizes building and moving fast, with an AI-first development culture, competitive compensation, equity, and comprehensive benefits.
What You Will Do
- Design, build, and optimize components of Conviva’s high-scale, real-time data platform.
- Turn deep systems knowledge or strong mathematical foundations from research or open-source work into production-grade engineering.
- Use AI coding and agentic tools (e.g., Claude Code, Cursor, Copilot) as a standard part of your workflow, for prototyping, code review, design exploration, and technical documentation.
- Contribute to AI/agentic capabilities: LLM pipelines, agent observability, intelligent data modeling.
- Take part in design reviews, and learn from code reviews and design pairing with senior engineers.
- Write high-quality, well-tested code and follow CI/CD best practices.
- Partner with Product and cross-regional engineering teams to translate business needs into scalable solutions.
- Communicate technical ideas and tradeoffs clearly in English.
Who You Are
- PhD (new graduates welcome) in distributed systems, AI/ML, or mathematics / applied mathematics / statistics from a top university, or an outstanding Master’s graduate with published papers at top venues in systems, databases, algorithms, or statistics.
- Good understanding of engine internals (query engines, storage engines, stream processing, distributed systems), or deep mathematical and algorithmic strength (e.g., optimization, probability, statistics, algorithm design) that you can apply to data systems, demonstrated through research, publications, open-source contributions, or hands-on experience with big data stacks such as Spark, ClickHouse, Druid, and Kafka.
- Familiarity with LLM and AI agent systems, and eagerness to build with them.
- Proficient in at least one of Python, Go, Java, Scala, or Rust.
- Actively uses AI coding tools (Cursor, Claude Code, GitHub Copilot) in daily work.
- Curious, self-driven, and comfortable with ambiguity; able to work with distributed teams across time zones.
- Excellent English communication skills, both verbal and written.
Bonus Points
- Publications at top systems/database venues (VLDB, SIGMOD, OSDI, SOSP, EuroSys, ATC), or top algorithms/ML/statistics venues.
- Meaningful contributions to Apache big data projects.
