Senior Backend Engineer, Experimentation

About the Job:

LaunchDarkly is seeking a Senior Backend Engineer to join our Experimentation team.

The Experimentation team is building one of the company’s most strategic product areas: a platform that helps leading engineering organizations move beyond intuition and make product decisions with real statistical confidence.

Sitting at the intersection of large-scale systems, data science, and user experience, the team is creating a best-in-class experimentation product that lets customers set up, manage, and analyze experiments with ease while still earning the trust of even the most rigorous data teams.

From warehouse-native analysis to experimentation workflows built on top of LaunchDarkly’s massive feature management scale, this team is tackling ambitious technical problems with visible customer impact and a clear opportunity to define the future of modern software experimentation.

As a Senior Backend Engineer, you will design and operate the services that power this product, contribute to technical direction, and help deliver new functionality to customers.

You will work closely with product managers, designers, data scientists, and engineers across LaunchDarkly to solve complex, data-intensive problems with meaningful customer impact.

Responsibilities:

• Design, build, and operate scalable backend services and APIs that power LaunchDarkly’s Experimentation product.
• Own backend components across their lifecycle, including technical discovery, design, implementation, testing, deployment, monitoring, incident response, and continuous improvement.
• Build and evolve systems supporting experiment setup, event data ingestion, metric computation, results processing, and results presentation.
• Contribute to architectural decisions and technical proposals, making thoughtful trade-offs around scalability, reliability, performance, cost, and maintainability.
• Partner with product managers, designers, data scientists, and adjacent engineering teams to translate customer needs and product goals into reliable technical solutions.
• Collaborate with Data Platform, Warehouse Integrations, SDK, and other teams on shared data flows, services, and cross-team dependencies.
• Investigate complex production issues, identify root causes, and implement durable fixes.
• Improve observability, testing, deployment safety, operational processes, and the reliability of the systems you build.
• Participate in the team’s on-call rotation and take ownership of production systems in a you-build-it-you-run-it culture.
• Support teammates through thoughtful code reviews, design reviews, knowledge sharing, and informal mentorship.

Qualifications:

• 6+ years of professional software engineering experience, including significant experience building and operating backend services in production.
• Fluency using AI tools in software engineering workflows, including the judgment to direct, evaluate, and validate AI-generated output.
• Experience designing and delivering customer-facing systems that are scalable, reliable, observable, and maintainable.
• Strong programming experience in Go or a comparable backend language such as Python, Rust, or C++. Our team is using Go.
• Experience with distributed systems, event-driven architectures, data pipelines, APIs, data modeling, or data-intensive services.
• Familiarity with analytical, operational, or warehouse data stores such as ClickHouse, Postgres, Snowflake, Redshift, BigQuery, Databricks, or equivalent technologies.
• Experience diagnosing production issues and improving system reliability through metrics, logs, traces, alerting, and other observability practices.
• Experience working in a cloud environment and with infrastructure-as-code or equivalent deployment and operations tooling.
• Ability to take an ambiguous problem from discovery and scoping through design, implementation, launch, and ongoing operation.
• Clear, thoughtful communication and a collaborative approach to working with technical and non-technical partners.
• Experience with experimentation, A/B testing, analytics, data platforms, or similarly data-intensive products.

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