• 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.

• You'll help build PostHog's observability suite: Logs (live and growing fast), Traces (in alpha), and Metrics (landing soon); the products that let our customers, and their AI agents, understand, debug, and self-heal their own software. • This is the foundation for self-driving, self-healing products, and we're building most of it from scratch. The core challenge is easy to say and hard to do: ingest, store, and retrieve enormous volumes of telemetry; fast, reliably, and cost-effectively. Getting data in is the easy half; getting it back out efficiently at petabyte scale, without melting the infra bill, is the real game. We're already handling terabytes of data and it's growing! • You won't be maintaining a corner of someone else's system. You'll own a product area end-to-end, taking it from alpha -> beta -> GA, making the architecture calls, and shipping in the hot path where your code decides whether customers have a good day. You'll work across all three products and go deep on one.