• Design and build scalable, fault-tolerant backend services for payment processing • Own end-to-end delivery of payment features • Partner with engineers and product managers to translate product vision into technical plans • Drive improvements to system reliability and performance • Contribute to engineering quality through code reviews and best practices

• Participate in client discovery and technical assessment meetings as the lead Ruby on Rails subject matter expert. • Analyze existing Ruby on Rails applications, architecture, and codebases to identify risks, technical debt, and improvement opportunities. • Lead system takeover assessments and evaluate legacy applications. • Develop technical roadmaps, modernization strategies, and implementation recommendations. • Provide architectural guidance for cloud-native and serverless environments hosted on Google Cloud Platform (GCP). • Collaborate with stakeholders to translate business requirements into scalable technical solutions. • Evaluate current infrastructure, deployment processes, and application performance. • Recommend best practices for maintainability, scalability, security, and operational efficiency. • Produce technical documentation, architecture recommendations, and implementation plans. • Support engineering teams throughout project planning and execution phases when required.

• Build, improve, and operate backend services that power LaunchDarkly’s Flag Delivery systems. • Contribute to systems that support streaming and polling delivery models for LaunchDarkly SDKs. • Debug production issues, improve service reliability, and help the team maintain strong standards around latency, availability, observability, and operability. • Work with technologies and patterns common to modern distributed backend systems, including caching layers, network services, concurrency, failure handling, and cloud infrastructure. • Collaborate closely with partner teams including SDK, Platform, SRE, Security, and Enterprise to deliver improvements across the broader platform. • Participate in the on-call rotation and take ownership of the systems you help build. • Learn the existing architecture deeply and make pragmatic improvements that increase system clarity, performance, and maintainability. • Use AI as part of your engineering workflow with sound judgment, including knowing when to use it, how to direct it effectively, and how to verify or reject its output. • Reason clearly about code, architecture, and whole-system behavior even when AI is in the loop.

• Design, build, and maintain scalable backend services using Elixir and Phoenix. • Develop highly available APIs and distributed systems that power critical platform functionality. • Build and optimize data pipelines, workflows, and background job processing systems. • Collaborate with AI, Data Science, and Product teams to bring intelligent automation capabilities into production. • Improve system observability, monitoring, reliability, and operational excellence. • Participate in architectural discussions and influence technical direction across the platform. • Help establish engineering best practices around testing, deployment, performance, and maintainability. • Mentor engineers and contribute to a collaborative, high-performing engineering culture. • Leverage AI-assisted development tools to improve productivity, quality, and delivery velocity.