01
about_the_role About the role
Revyl gives developers and AI agents cloud iOS and Android environments where they build, run, inspect, and verify mobile applications. Behind that experience is a distributed compute platform spanning GCP, physical Mac infrastructure, simulators, emulators, build runners, streaming, and test execution.
We’re entering a period where our infrastructure needs to support significantly more customers, workloads, and compute. You’ll be responsible not only for operating that infrastructure, but for figuring out how it evolves: identifying bottlenecks and scaling limits, and owning the technical roadmap while moving fluidly between understanding current systems, designing what comes next, and building it hands-on.
02
what_youd_work_on What you’d work on
- Define the infrastructure scaling strategy: analyze the current architecture, identify what breaks under increased load, and build the roadmap to scale ahead of demand.
- Capacity planning and modeling that translates customer and partnership growth into compute, storage, network, device, and hardware requirements.
- Systems for provisioning, scheduling, managing, and recycling large fleets of iOS simulators, Android emulators, and physical compute.
- Distributed workload orchestration for builds, tests, agent sessions, and interactive workloads across heterogeneous compute pools.
- The GCP infrastructure behind our APIs, control plane, workflow execution, storage, networking, and supporting services.
- Finding and eliminating bottlenecks with production data, from CPU, memory, disk, and network through scheduler throughput, database performance, and host capacity.
- Preparing the platform for step-function growth with load tests, failure tests, and capacity plans for large new customers and partnerships.
03
what_were_looking_for What we’re looking for
- Experience taking an infrastructure platform from one stage of scale to the next.
- 5+ years of software engineering, infrastructure, platform engineering, or SRE experience with significant technical ownership.
- You’ve helped scale production infrastructure or a compute platform through a meaningful increase in load.
- You can analyze an existing architecture, identify scaling constraints, and prioritize a technical roadmap.
- You understand capacity planning and how to translate business forecasts into infrastructure requirements.
- You make architectural decisions under uncertainty and validate assumptions with instrumentation, benchmarking, load testing, and production data.
- You’ve built or operated distributed systems at meaningful scale.
- You’re a strong software engineer who builds infrastructure services and control-plane systems, not just configures tooling.
- You understand scheduling, queues, worker pools, concurrency, backpressure, resource allocation, and failure recovery.
- Deep experience with cloud infrastructure on GCP, AWS, or Azure.
04
what_success_looks_like_in_the_first_year What success looks like in the first year
- We have a clear model of the capacity and architecture needed to support the next stages of growth.
- Major scaling limits are known before a customer hits them.
- Concrete capacity and load plans exist for large new customers and partnerships before launch.
- The platform handles an order of magnitude more concurrent compute without a proportional increase in operational work.
- Common infrastructure failures are detected and remediated automatically.
- Device scheduling and capacity management are predictable instead of reactive.
- Infrastructure projects are prioritized by real scaling constraints rather than the most recent incident.
- The team spends substantially less time firefighting, and the Device Cloud becomes a platform that scales repeatably instead of being reinvented with each growth phase.