Senior Software Engineer - Node.js/Vue.js

This role is best suited for a Senior-level software engineer with 5+ years of experience who is confident building and operating distributed systems using Node.js, Vue.js, and TypeScript. It fits someone experienced with microservices, cloud-native infrastructure, databases, caching, messaging systems, and CI/CD, who enjoys owning end-to-end flows, improving reliability and performance, and addressing technical debt. The position will appeal to engineers who value collaboration, clear communication, proactive problem-solving, and maintaining high code quality in a fully remote, agile environment.

1. What is your experience building backend services with Node.js in a microservices architecture?
   I’ve spent several years building Node.js services in TypeScript, typically using Express or NestJS, with clear module boundaries and domain-driven design principles. I’ve implemented REST and event-driven services that communicate over queues (e.g., SQS/SNS, RabbitMQ) and use Postgres/Redis for persistence and caching. I focus on clean contracts, observability (structured logging, metrics, tracing), and resilience patterns like retries, circuit breakers, and idempotency for at-least-once delivery flows.

2. How have you used Vue.js and TypeScript to implement complex frontends?
   I’ve built data-heavy single-page applications using Vue 2/3 with TypeScript, Vuex/Pinia for state management, and component-driven design. I structure the codebase around feature modules, create reusable UI components, and strongly type props, emits, and stores to catch issues at compile time. I pay a lot of attention to loading/error states, accessibility, and performance (lazy loading routes/components, avoiding unnecessary reactivity, and memoizing derived state).

3. Describe how you would design an end-to-end flow for processing and displaying restaurant orders in near real time.
   I’d expose a Node.js service that ingests orders via a well-defined API or message queue, validates and normalizes them, then persists to Postgres with appropriate indexing and uses Redis for hot paths like “latest orders per location.” Events would be published via SNS/SQS (or similar) for downstream consumers (analytics, notifications). On the frontend, a Vue app would subscribe to a lightweight API that supports polling or server-sent events/WebSockets for near real-time updates, with local state optimized for fast filtering and sorting by status, location, and time.

4. What is your approach to performance tuning in a distributed Node.js system?
   I start by measuring: profiling hot endpoints, checking APM traces, and reviewing database/query metrics. Common optimizations include reducing chatty calls with batching, adding appropriate indexes, caching computed results in Redis, and streaming large responses instead of buffering. I also look at CPU/event-loop utilization, avoid blocking operations, and ensure we use connection pooling and efficient serialization. At the system level, I apply backpressure, rate limiting, and horizontal scaling via Kubernetes with sensible resource requests and autoscaling rules.

5. How do you ensure reliability and observability for services that are critical to restaurant operations?
   I design services with graceful degradation and clear SLIs/SLOs in mind. Every service ships with structured logs, metrics (latency, error rate, throughput), and traces wired into centralized monitoring. I define health and readiness probes, and expose meaningful status endpoints. For incidents, I rely on dashboards and alerts that focus on user impact, not just infrastructure signals. Post-incident, I contribute to blameless retrospectives and fix the root cause (e.g., improving timeouts, adding safeguards, or hardening dependencies) rather than just patching symptoms.

6. What is your experience using technologies like Postgres, Redis, and Elasticsearch together?
   I’ve used Postgres as the primary source of truth, designing normalized schemas and tuned indexes for transactional workloads. Redis has typically been used for low-latency caching, distributed locks, and ephemeral data like sessions or rate limits. Elasticsearch (or OpenSearch) has been my choice for full-text search, aggregations, and log analytics. I’m careful about consistency between Postgres and Elasticsearch, often using event streams or change-data-capture patterns, and I monitor cache hit rates and index performance to keep the whole stack healthy.

7. How do you approach automated testing for a Node.js/Vue.js application?
   I layer tests: unit tests for pure logic and small components (Jest/Vitest), integration tests for service boundaries (e.g., API + DB using test containers or an in-memory setup), and end-to-end tests for critical user flows (Cypress/Playwright). On the frontend, I test Vue components with realistic props and state, focusing on behavior rather than implementation details. I keep tests fast and reliable, run them in CI on every PR, and use coverage and flakiness as signals to refactor both tests and code.

8. Describe a time you led or heavily influenced an architectural decision in a distributed system.
   In a previous role, I led the migration of a monolithic order-processing pipeline to a set of Node.js microservices behind a message bus. I evaluated options with the team, proposed a phased strangler-fig approach, and defined service boundaries, event contracts, and operational practices. I implemented the first service, documented patterns (logging, metrics, retries, idempotency), and mentored others as they built additional services. The result was improved resilience, easier independent deployments, and clearer ownership per domain.

9. How do you collaborate with product managers and non-technical stakeholders in a remote environment?
   I make communication explicit and frequent: I clarify requirements with examples, propose technical options with trade-offs in plain language, and share early prototypes or screenshots to validate we’re aligned. I use async updates (docs, tickets, short Loom videos) combined with focused sync meetings. During incidents or time-sensitive work, I keep stakeholders updated on impact, timelines, and mitigation steps. My goal is to be a trusted partner who translates customer needs into pragmatic technical solutions.

10. Why are you interested in joining Olo and working on tools that support restaurant operations?
    I’m excited by products that operate at scale and have a very tangible, real-world impact. Helping restaurants run smoother, serve guests better, and handle orders reliably in real time is a meaningful technical challenge. Olo’s stack—Node.js, Vue.js, TypeScript, Postgres, Redis, and Kubernetes—matches my experience and interests, and the focus on high-quality, reliable systems and collaborative culture is exactly the environment where I do my best work and can contribute from day one.

This position is a strong match for a senior full-stack JavaScript engineer in Northern Ireland who wants to own end-to-end features in a Node.js + Vue.js microservices environment—someone comfortable designing and scaling distributed systems with TypeScript, Postgres, Redis, Elasticsearch, SNS/SQS, Kubernetes, and CI/CD, who enjoys collaborating with product and ops to build tools that power day-to-day restaurant operations, proactively monitor and debug production issues, pay down technical debt, and drive best practices in code quality, performance, and agile delivery on a fully remote, restaurant-focused SaaS platform.