Full Stack Engineer - Observability
LaunchDarkly · Remote (United States) · Measure Engineering
About this role
LaunchDarkly is hiring a mid-level Full Stack Engineer in the software engineering function as a remote position. The posting calls out experience with TypeScript, Go, React, LLMs. Compensation is listed at $136,500–$187,660 per year.
- Role
- Full Stack Engineer
- Function
- software engineering
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- Remote (United States)
- Work mode
- Remote
- Department
- Measure Engineering
More roles at LaunchDarkly
Job description
from LaunchDarkly careersAbout the Job:
LaunchDarkly is looking for a Full Stack Engineer to help build and expand Vega, our AI-powered platform that surfaces insights and automates actions across LaunchDarkly products. This is a greenfield opportunity: you'll help evolve Vega from an Observability-focused assistant into a cross-product platform that serves Feature Management customers and powers a new, usage-based SKU.
You'll build the surfaces, APIs, and agent infrastructure that make Vega and the whole Observability platform broadly valuable—enabling capabilities like AI-driven dashboard creation, flag cleanup automation, and sandboxed agent execution. You'll work across the full stack (React/TypeScript UI, Go services, data pipelines) and collaborate closely with product, design, and other engineering teams to shape how AI capabilities land across LaunchDarkly. Additionally, you’ll work on other Enterprise-grade capabilities for the Observability platform to help drive customer activation and success.
What You'll Work On:
- Expand Vega beyond Observability into Feature Management, including the flag cleanup agent as a cross-product capability
- Support enterprise capabilities for the Observability platforms: building data import and export pipelines to connect O11y to other platforms and enabling new customer workflows.
- Build a platform that other teams can contribute to—defining contribution patterns, shared infrastructure, and safe, sandboxed AI agent execution
- Enable dashboard creation via natural language prompts, using existing Vega infrastructure as a foundation