Senior Backend Engineer

About SuperNova SuperNova is developing a mobile-first super app that empowers Brand Ambassadors (BAs) — independent sales promoters and recruiters. The platform streamlines the entire BA lifecycle: recruitment, onboarding, sales training, product distribution, sales enablement, payments, performance monitoring as well as team and community growth. SuperNova will also support agencies (SalesWorks franchisees) with the same set of services to manage their Brand Ambassadors at scale. About the role We are looking for a Senior Backend Engineer to take a leading role in building the SuperNova durable workflows and micro services. You will own features implementation end-to-end as well non-functional requirements such as security, performance and reliability. You’ll work closely with Product and SDET/QA to ensure features are delivered to agreed specifications and to the highest quality, both functionally and non-functionally. The codebase is an AI-native monorepo with a local-first mobile client today and backend services planned as Architecture Decision Records (ADRs); you will work within those conventions and help evolve them as the product grows. This role is ideal for someone who has extensive hands-on experience architecting and building durable workflows and microservices, deeply understands modern monorepo structure and hermetic build systems, practices rigorous testing (including Behaviour-Driven Development), and is fluent in configuring and deploying cloud-native services on Google Cloud—ideally with Encore. Backend development & architecture The ideal candidate will have experience of the following development paradigms & architectural design patterns (example implementation frameworks suggested): Developer experience (hermetic build process) — Possibly Bazel for hermetic, incremental builds and affected targets, just recipes and local development via Docker (docker compose). Minimal dependencies — We add packages only when they solve a clear, recurring problem and provide measurable value. Prefer the existing stack and well-understood tools before introducing new ones.Cloud native engineering — Combination of managed services, serverless compute, and durable workflow execution self-hosted + custom services, containerised for local/prod parity).Durable workflows & microservices — Deep experience designing, implementing, and operating long-running, reliable, observable workflows and loosely-coupled services (Temporal-style orchestration or equivalent; event-driven patterns; saga/compensation where needed).GitOps & Continuous Integration — Maintain an improve our GitOps model (AI-native monorepo as the single source of truth for both application code and infrastructure-as-code) so every merge triggers reproducible, auditable deployments to Google Cloud via Encore and declarative pipelines. Enforce hermetic builds, pipelines that run identically locally and in CI, comprehensive test suites (unit, integration, contract/API and Behaviour-Driven Development), and automated quality gates covering security, performance, reliability and cost. Relentlessly raise the quality bar—reducing flakiness, increasing meaningful coverage, tightening observability and refining developer experience—so the team can ship durable workflows and microservices with speed and confidence. What we expect at senior level Technical AI Native development. Using appropriate models with your favourite CLI and IDE not only to write code to but to interrogate product specifications, automate testing and drive productivity in all aspects of your work.Extensive experience architecting and shipping durable workflows and microservices in production.Mastery of the build process: hermetic builds, remote caching, incremental/affected testing, and local development via Docker Compose.Experience deploying and operating services on Google Cloud, with preference for Encore-based cloud-native development.Solid testing habits — testable architecture, provider overrides, meaningful widget tests.Ability to read and write ADRs and explain trade-offs clearly. Collaboration Improve developer experience (just recipes, docs, CI) when you hit friction and let others know when you discover sources of friction.Effectively manage your communication and ‘work outloud’. Respond in a timely fashion to requests for information and assistance. Be present in third-party support platforms (slack, discord, etc) and build relationships with technology vendors. Work effectively with AI coding tools — the repo is structured so agents can follow ADRs and feature-module conventions. Automate workflows with AI engagement (code review, pull requests, writing and executing tests, etc) Mindset Bias toward simplicity — focus on delivery; avoid over-abstraction.Data-driven decisions — instrument everything so design and operational choices can be validated.Ownership of the full lifecycle — from local development through production reliability, drive your deliverables.High Agency & Self-Reliance — act independently when necessary and find ways to remove obstacles when there is no clear playbook or support. Nice to have Hands-on experience with Temporal, Cadence or equivalent durable workflow orchestration engines at scale.Deep familiarity with Encore (or similar cloud-native backend frameworks) and deploying/operating services on Google Cloud.Proven experience with Bazel monorepos, Dagger pipelines, GitOps tooling (ArgoCD, Flux, etc.) and hermetic CI/CD.Operating self-hosted identity providers (Zitadel, Keycloak or similar) and integrating them securely into microservices.Backend-focused feature-flag systems (Flagsmith, OpenFeature, LaunchDarkly server-side SDKs).Prior work on high-scale payments, event-driven architectures, multi-tenant or multi-sided platforms (individual contributors + agencies/managers).Experience migrating legacy backend services while preserving data integrity, API contracts and zero-downtime cutovers.Strong observability practices (OpenTelemetry, Prometheus, Grafana) and SRE-level reliability for microservices and durable workflows.