Backend Engineer, Metrics Hybrid - San Francisco Bay Area

In the software world today, teams ship software faster than ever, but the hard part is doing it without breaking things. New features, new services, new dependencies all adds risk. Launch Darkly gives engineers a way to move quickly while keeping control. You can roll changes out incrementally, spot problems early, and learn what actually makes the product better.

AI is starting to amplify that need. Models behave differently in production than they do in a notebook, and teams need a safe way to test ideas, gather real signals, and pull back if something goes sideways. The same tools that help teams ship traditional features end up being just as useful for AI-driven ones.

As a P2 on Metrics, you’re building the part of the platform that turns raw events into meaningful LD units that can be turned into measurements. Your work will support safer releases, clearer experimentation, and faster learning across both traditional software and emerging AI workloads. This is a chance to grow as an engineer while contributing to infrastructure that modern teams depend on every day.

Build and maintain backend features within the Metrics services, following established patterns and designs.

Help develop internal APIs that connect customer events to experimentation and release-safety workflows, with guidance from senior engineers.

Work with data pipeline teams to understand how events flow through ingestion, storage, and querying, and make targeted contributions where needed.

Assist in integrating event-driven capabilities into areas like AI Configs, Observability, and Experimentation.

Support service reliability work by adding tests, improving logs, tuning alerts, and helping investigate issues during development.

Participate in code reviews, design discussions, and planning sessions, asking clear questions and contributing thoughtfully.

Learn the operational side of running distributed systems, including debugging, monitoring, and safe rollout practices.

Experience with at least one server‑side programming language and interest in working with Go.

Ability to build and maintain basic RESTful APIs using existing patterns.

Understanding of core computer science concepts such as data structures, concurrency, and distributed systems basics.

Familiarity with databases or event stores like Postgres, Click House, Elastic Search, Snowflake, or similar.

Exposure to data or event-processing tools such as Kinesis, Airflow, Spark, Lambda, Flink, or equivalents.

Basic experience with infrastructure‑as‑code tools like Terraform, or willingness to learn.

Familiarity with observability tools like Datadog. Able to read dashboards and debug with guidance.

Willing to commute to Oakland twice a week

Exposure to CI systems such as Circle

CI or Spinnaker.

Early familiarity with experimentation frameworks or statistical ideas.

Target pay ranges based on Geographic Zones
* for Level 2:

• Zone 1:
  San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $136,500 - $187,660**
• Zone 2:
  Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $122,800 - $168,850**
• Zone 3:
  All other US locations - $116,000 - $159,500**

Launch Darkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location.

* Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas.

** Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary.

Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The Launch Darkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong.

Developers can target product experiences to any customer…