Software Engineer, Database Reliability & Performance

InfluxData•San Francisco, CA

3d•$100,000 - $168,000•Remote

About The Position

InfluxData is seeking a highly skilled individual contributor (IC) with background knowledge on Database and QA to join the Database Performance and Reliability Team. In this role, you will be working closely on the InfluxDB Enterprise 3 product and be instrumental in ensuring the reliability, correctness, stability and high performance of our core database platform across complex data models and workloads. AI is integrated into our daily workflow, proficiency and hands-on experience with AI-driven tools and techniques are essential.

Requirements

Coding Proficiency: Deep hands-on experience developing using Rust (highly preferred) or a desire to learn Rust with system experience in [C++|Golang].
Strong QA and Testing Experience: Proven track record in performance, regression, and reliability validation frameworks. Ability to confidently establish repeatable baselines for distributed data systems.
Solid understanding of CS fundamentals with minimum Bachelor’s degree and 5 years of work experience.
Comfort using modern AI assistants and tools (e.g., Claude) for quick troubleshooting, on-the-fly utility generation, and analyzing logs and pattern anomalies at scale.
Competency working with containerized environments and orchestration frameworks like Docker and Kubernetes, alongside modern CI utilities such as CircleCI.
Excellent verbal and written communication skills, with the ability to effectively work asynchronously.

Nice To Haves

Building distributed systems.
Working with database internals and various cloud vendors.
Participating in an on-call rotation.
Working with distributed products and teams.

Responsibilities

Own and execute automated reliability, regression, and correctness test workflows within the CI/CD pipeline.
Implement and maintain repeatable test contracts utilizing frameworks like internal tools to validate query accuracy, product lifecycle, database compactions, and recoverability.
Differentiate between standard functional validation and exhaustive reliability testing—simulating real-world customer workloads, database restarts, memory exhaustion, and deployments.
Collaborate closely with core developers to convert high-level engineering specifications and customer root-cause analyses into formal, repeatable test constraints.
Investigate complex performance data variations, capture system profiles, and proactively identify architectural bottlenecks before production deployment.
Be part of an on-call rotation when need arises.
Develop and Review automated reports on a regular cadence to flag suspicious query latency regressions, data divergence bugs, or resource starvation issues to relevant engineering stakeholders.