SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 248,000 - 279,000 / annual
Discord is seeking a Staff Software Engineer to lead the development of its next-generation experimentation platform. This is a high-impact role where you'll design, build, and support core systems that enable data-informed decision-making across the company. You'll own the full stack—from core services and data pipelines to configuration tooling, statistical analysis tools, and user experience—while incorporating state-of-the-art AI-assisted experimentation workflows.
Key responsibilities include:
- Architecting and building Discord's experimentation platform from the ground up, including services, data pipelines, configuration tools, and statistical analysis capabilities
- Leading and mentoring engineers, fostering their growth and technical development
- Collaborating with non-technical stakeholders across the company to understand experimentation needs
- Influencing product telemetry practices to support robust experimentation
- Delivering business results by enabling teams to experiment on features, machine learning models, and product improvements
- Building high-scale data systems that serve millions of daily active users
You should bring 7+ years of full-stack software engineering experience, with proven expertise in building internal tools and A/B testing frameworks. Experience building or working with experimentation platforms is essential; having built core components from scratch is a major plus. You'll need strong technical leadership skills—the ability to take high-level goals and deliver shippable solutions while managing complex technical projects. Proficiency in Python and SQL is required, with TypeScript or Rust as bonuses. You should have experience with diverse datastores (relational, NoSQL, data warehouse solutions) and building systems with strong data governance, privacy, and security controls.
Bonus qualifications include experience with human-in-the-loop AI systems, cloud platforms (GCP/AWS), modern data processing stacks, full-stack development, and deep knowledge of statistics or large-scale data processing.
