Senior Full Stack Engineer, Observability

NetBox Labs is seeking a Full Stack Engineer to join our rapidly expanding engineering team. We have multiple positions open at different seniority levels across several teams.

About NetBox Labs

NetBox Labs builds the next generation of network automation tools for modern infrastructure teams, with NetBox as the network source of truth at the center. The Observability team builds the products that connect that source of truth to what is actually running on the network:

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NetBox Discovery finds devices, interfaces, and other network entities.

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NetBox Assurance brings discovered data into NetBox and helps operators spot drift between intended and actual state, review changes, and decide what to accept.

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Fleet Management and the Orb agent deploy, configure, and manage the agents that collect discovery and telemetry data from customer networks. These agents use SNMP, gNMI, and other device interfaces.

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Diode is the ingestion pipeline that moves that data into NetBox reliably.

We're hiring a Full Stack Engineer who can work across the whole path, from the agents and services that collect network data to the interfaces operators use to understand and act on it.

Role overview

You'll join the Observability team and take ownership of features end to end. That covers:

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Go and Python services and gRPC APIs in the control and data planes.

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The data flows that carry discovery and telemetry results into NetBox.

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The React dashboards and interfaces where customers monitor network and device health, explore telemetry, review discovered data, and manage their agent fleet.

You'll work closely with product, design, and other engineering teams, and you'll help run the services the team owns in production.

This role is hands-on. You'll ship features across the stack, improve reliability and performance, and help define the architecture and practices needed to scale network discovery and assurance to large, complex customer environments.

What you'll do

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Design, build, and operate backend services in Go and Python for discovery, assurance, fleet management, and data ingestion.

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Define and evolve gRPC and REST APIs with clear, versioned contracts using Protocol Buffers and OpenAPI.

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Build React and TypeScript monitoring and telemetry dashboards that show device, interface, and network health in real time, with time-series charts, status views, and drill-down from fleet to device to interface.

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Design dashboard experiences that help operators spot problems fast: sensible defaults, time-range and filter controls, thresholds and alert states, and clear links from a metric to the underlying device in NetBox.

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Work with backend engineers on the query and aggregation APIs that power dashboards, so they stay fast with large fleets and high-frequency telemetry.

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Build type-safe integration between frontend and backend using generated API clients, shared schemas, and consistent error and auth handling.

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Participate in the team's on-call rotation for the services it owns.

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Add automated tests across the stack (unit, integration, contract, and end-to-end) and enforce quality gates in CI.

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Collaborate with product managers, designers, customer-facing teams, and other engineering teams. The goal is for features to solve real network operator problems.

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Use AI-enabled development tools and agentic workflows day to day to speed up design, coding, testing, code review, and incident triage, and help the team adopt them effectively and safely.

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Review code, mentor teammates, and share best practices for service design, API design, and frontend engineering.

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Participate in planning processes and help shape the roadmap.

What we're looking for (minimum qualifications)

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Experience: 5+ years of professional software engineering, with meaningful production experience on both backend and frontend.

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Backend

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Production experience with Go and Python: strong in at least one and working proficiency in the other.

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Hands-on experience designing and operating gRPC services with Protocol Buffers, including schema evolution and backward compatibility, streaming RPCs, deadlines, interceptors/middleware, and error handling.

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Experience building distributed, event-driven systems, including message queues (e.g., RabbitMQ or Kafka), asynchronous job processing, and idempotent data ingestion.

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Frontend (monitoring and telemetry dashboards)

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Strong React and TypeScript skills, including component composition, state management, and typing best practices.

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Proven experience building monitoring, observability, or analytics dashboards: time-series charts, heatmaps, status and health views, and drill-down navigation.

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Hands-on experience with data visualization libraries (e.g., D3, ECharts, Recharts, uPlot, or Visx).

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Experience rendering large or high-frequency datasets performantly, using techniques such as downsampling, virtualization, and canvas or WebGL rendering.

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Experience handling real-time data in the browser via WebSockets, server-sent events, or gRPC-Web streaming, along with caching and refresh strategies (e.g., TanStack Query).

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Modern CSS (TailwindCSS or similar utility-first frameworks), responsive layout, and practical accessibility (WCAG), including color-blind-safe palettes and accessible charts.

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Automated frontend testing with Jest and React Testing Library, including visual regression testing for charts and dashboards.

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AI-enabled development

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Practical, regular use of AI coding assistants and agents (e.g., Claude Code, Cursor, GitHub Copilot) across the development lifecycle: writing and refactoring code, generating tests, reviewing changes, and writing documentation.

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Good judgment about when to trust AI output, including verifying generated code, keeping changes reviewable, and protecting sensitive data such as customer network information and credentials.