[All remote jobs](https://jobicy.com/jobs.md)[![LaunchDarkly logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/115b7a27-221.jpg)](https://jobicy.com/company/launchdarkly.md)[LaunchDarkly](https://jobicy.com/company/launchdarkly.md) # Senior Backend Engineer, Experimentation Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/launchdarkly.md)ShareRemote from[USA](https://jobicy.com/job-region/usa.md)SalaryUSD 163k–263,670 / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished1 Nov 2026Apply before1 Dec 2026Listing views41Application actions3Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. LaunchDarkly is seeking a senior backend engineer to build and operate the services behind its experimentation platform. The role covers scalable APIs, event ingestion, metric computation, results processing, and reliable production operations. It requires strong experience with Go or a comparable backend language, distributed systems, data-intensive services, cloud infrastructure, and observability. The engineer will partner closely with product, design, data science, and platform teams while contributing to architecture, incident response, mentoring, and on-call ownership. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior, end-to-end ownership role involving production distributed systems, data pipelines, experimentation analytics, and on-call responsibility. Candidates must make architecture trade-offs independently while collaborating across several technical and non-technical disciplines. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job median (per year)Highly competitive$213,335US market range (per year)$165k–$255k0$280.50k AI insightThe yearly pay period is inferred from the job context; it was not explicitly stated by the employer. The posting discloses a USD 163,000–263,670 target salary range across US geographic pay zones. The annual cadence is inferred from the stated US senior-engineering compensation levels because the posting labels the figures as salary but does not explicitly state a pay period. Estimated US market compensation for a senior backend engineer working on data-intensive distributed systems is USD 165,000–255,000 annually. ## Core skills Skills and capabilities most closely associated with this opportunity. [Go](https://jobicy.com/jobs?search_keywords=Go.md)[Backend Engineering](https://jobicy.com/jobs?search_keywords=Backend%20Engineering.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[Event-Driven Architecture](https://jobicy.com/jobs?search_keywords=Event-Driven%20Architecture.md)[API Design](https://jobicy.com/jobs?search_keywords=API%20Design.md)[Data Pipelines](https://jobicy.com/jobs?search_keywords=Data%20Pipelines.md)[Data Modeling](https://jobicy.com/jobs?search_keywords=Data%20Modeling.md)[Cloud Infrastructure](https://jobicy.com/jobs?search_keywords=Cloud%20Infrastructure.md)[Infrastructure as Code](https://jobicy.com/jobs?search_keywords=Infrastructure%20as%20Code.md)[Observability](https://jobicy.com/jobs?search_keywords=Observability.md)[Incident Response](https://jobicy.com/jobs?search_keywords=Incident%20Response.md)[PostgreSQL](https://jobicy.com/jobs?search_keywords=PostgreSQL.md)[ClickHouse](https://jobicy.com/jobs?search_keywords=ClickHouse.md)[A/B Testing](https://jobicy.com/jobs?search_keywords=AB%20Testing.md)[System Design](https://jobicy.com/jobs?search_keywords=System%20Design.md) Sample interview questionsHow would you design a service to ingest high-volume experimentation events while preserving reliability and data quality?I would use a durable, partitioned event stream with idempotent producers and consumers, schema validation, and a dead-letter path for malformed records. I would define ordering and deduplication requirements up front, expose ingestion lag and error metrics, and build replay capabilities so downstream computations can be corrected safely. Describe how you would investigate a discrepancy between an experiment’s expected and reported metric results. I would first validate the metric definition, experiment assignment logic, and analysis window. Then I would trace representative events through ingestion, transformation, and storage using logs, traces, and reconciliation queries, checking for late data, duplicates, filtering changes, or aggregation errors before implementing a tested fix and backfill plan. What trade-offs would you consider when selecting a datastore for experimentation analytics? I would consider query latency, ingestion throughput, cardinality, retention, cost, consistency needs, and how well the store supports the required aggregations and segmentation. For example, an analytical columnar store may suit high-volume metric queries, while a relational store can hold configuration and transactional workflow data. How do you approach operating a service in a you-build-it-you-run-it environment? I treat operational readiness as part of delivery by defining service-level objectives, dashboards, alerts, runbooks, safe deployment controls, and rollback procedures before launch. During incidents, I prioritize customer impact reduction, communicate clearly, identify root causes, and follow through with durable corrective actions. How would you use AI tools in a senior software engineering workflow without compromising quality? I would use AI tools to accelerate exploration, draft tests, summarize unfamiliar code, and generate implementation alternatives, but I would validate all output through design review, code review, testing, security checks, and direct understanding of system behavior. The engineer remains accountable for correctness, maintainability, and production impact. Opportunity details ## About this role. ### 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. Pay: Target pay ranges based on Geographic Zones* for Level 4: * Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle – $191,800 – $263,670** * Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago – $172,600 – $237,270** * Zone 3: All other US locations – $163,000 – $224,070** LaunchDarkly 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. ### About LaunchDarkly: 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 LaunchDarkly 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 segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare “big-bang” technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: * Improving the velocity and stability of software releases, without the fear of end customer outages * Delivering targeted experiences by easily personalizing features to customer cohorts * Maximizing the business impact of every feature through the ability to experiment and optimize * Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types * Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We’re building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at [hr@launchdarkly.com](mailto:hr@launchdarkly.com). Do you need a disability accommodation? Fill out this [accommodations request form](https://docs.google.com/forms/d/e/1FAIpQLSdYb_7upYMtdRVXzvXGHGfQw0pU2FNma-6Rwp-I6NjKm7SYNw/viewform) and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @[launchdarkly.com](http://launchdarkly.com) email addresses or via LinkedIn from “Verified Recruiter” accounts. Be cautious of emails from other domains. Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don’t click any links—visit [Careers | LaunchDarkly](https://launchdarkly.com/careers/) directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to [careers@launchdarkly.com](mailto:careers@launchdarkly.com). 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