Senior Software Engineer - Distributed Systems (Applied AI)

At Datadog, Batch Engineering owns something most engineers only dream about: a domain. They are responsible for the systems that apply signal finding models at scale, and are looking for a senior backend engineer to own and grow this space from our Paris hub.

You'd be architecting the scalable systems that power both internal data science and external customers, while building influence over a team that's tackling real, meaty infrastructure problems every day. The core here is Kafka and Flink while collaborating with data scientists on signal systems that work at scale. Most backend engineers work in one or the other; you'd own both end-to-end.

At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them.

• Design, build, and operate the backend systems that apply signal finding models at scale for internal data science teams and external customers.
• Own Kafka and Flink components end to end, from architecture and implementation through production reliability, performance, and evolution.
• Partner with data scientists to turn models and signal requirements into robust production workflows.
• Improve the scalability, observability, and operational resilience of data processing systems as usage grows.
• Lead technical decisions in your domain, collaborate across engineering teams, and help other engineers grow through design reviews and mentorship.
• You have significant backend engineering experience building and operating distributed systems in production.
• You have hands-on experience with Kafka and Flink, including designing or improving data processing pipelines at scale.
• You can reason through tradeoffs in throughput, latency, reliability, and maintainability, and turn those decisions into clear designs and working code.
• You enjoy collaborating with data scientists and engineering partners to translate open-ended requirements into dependable systems.
• You can take ownership of a technical area while sharing context, reviewing designs, and supporting the growth of teammates.
• You’re curious about using AI tools to improve how you build software and able to evaluate their output critically.

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