[Hiring] Senior Full Stack Engineer @NetBox Labs

Role Description

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.

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.

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

• Go and Python services and gRPC APIs in the control and data planes.
• The data flows that carry discovery and telemetry results into NetBox.
• The React dashboards and interfaces where customers monitor network and device health, explore telemetry, review discovered data, and manage their agent fleet.

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:

• Design, build, and operate backend services in Go and Python for discovery, assurance, fleet management, and data ingestion.
• Define and evolve gRPC and REST APIs with clear, versioned contracts using Protocol Buffers and OpenAPI.
• 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.
• 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.
• Work with backend engineers on the query and aggregation APIs that power dashboards, so they stay fast with large fleets and high-frequency telemetry.
• Build type-safe integration between frontend and backend using generated API clients, shared schemas, and consistent error and auth handling.
• Participate in the team's on-call rotation for the services it owns.
• Add automated tests across the stack (unit, integration, contract, and end-to-end) and enforce quality gates in CI.
• Collaborate with product managers, designers, customer-facing teams, and other engineering teams. The goal is for features to solve real network operator problems.
• 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.
• Review code, mentor teammates, and share best practices for service design, API design, and frontend engineering.
• Participate in planning processes and help shape the roadmap.

Qualifications

• Experience: 5+ years of professional software engineering, with meaningful production experience on both backend and frontend.
• Backend:
  • Production experience with Go and Python: strong in at least one and working proficiency in the other.
  • 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.
  • Experience building distributed, event-driven systems, including message queues (e.g., RabbitMQ or Kafka), asynchronous job processing, and idempotent data ingestion.
• Frontend (monitoring and telemetry dashboards):
  • Strong React and TypeScript skills, including component composition, state management, and typing best practices.
  • Proven experience building monitoring, observability, or analytics dashboards: time-series charts, heatmaps, status and health views, and drill-down navigation.
  • Hands-on experience with data visualization libraries (e.g., D3, ECharts, Recharts, uPlot, or Visx).
  • Experience rendering large or high-frequency datasets performantly, using techniques such as downsampling, virtualization, and canvas or WebGL rendering.
  • 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).
  • Modern CSS (TailwindCSS or similar utility-first frameworks), responsive layout, and practical accessibility (WCAG), including color-blind-safe palettes and accessible charts.
  • Automated frontend testing with Jest and React Testing Library, including visual regression testing for charts and dashboards.
• AI-enabled development:
  • 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.
  • 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.
  • Familiarity with prompting and context techniques that make AI tools effective on a real codebase, such as project instructions, specs, and structured workflows.
• Ways of working:
  • Good communication skills and a proven ability to work collaboratively in small, cross-functional teams.
  • Comfortable working in a fast-moving environment and contributing to product and technical decisions.

Nice to have

• Networking protocols and device interfaces:
  • Familiarity with networking protocols and concepts such as TCP/IP, DNS, DHCP, BGP, OSPF, VLANs, and LLDP/CDP.
  • Experience with network management and telemetry interfaces such as SNMP (MIBs, polling, traps), gNMI/gNOI, streaming telemetry.
• Network automation: Experience with NetBox, network automation frameworks (e.g., NAPALM, Nornir, Netmiko), or building agents that run in customer environments.
• Telemetry and observability: OpenTelemetry/OTLP, Prometheus, or time-series databases (e.g., Mimir, InfluxDB, ClickHouse), including query languages such as PromQL.
• Dashboard tooling:
  • Grafana panel or plugin development, or embedding third-party dashboards in a product.
  • User-configurable dashboards (saved views, custom layouts, dashboards as code).
  • Designing alerting and incident UX: thresholds, alert states, annotations, and event timelines.
• Building with AI:
  • Building AI-powered product features or internal tools using LLM APIs, such as natural-language queries over telemetry, anomaly explanations, or assisted troubleshooting.
  • Experience with the Model Context Protocol (MCP), tool-using agents, or agentic development frameworks and workflows.
  • Evaluating AI features for quality and reliability, such as eval suites and guardrails.

Company Description

NetBox Labs helps companies build and manage complex networks. We help customers accelerate network automation by delivering open, composable products and supporting the network automation community.

NetBox Labs is the commercial steward of open source NetBox, the world’s most popular network source of truth, and Orb, the next-generation open source network observability platform. Our products include:

• NetBox Enterprise, a fully supported self-managed NetBox with advanced features.
• NetBox Cloud, a secure, scalable, and reliable SaaS edition of NetBox.

NetBox powers thousands of companies, and NetBox Labs is backed by investment from Notable Capital (formerly GGV), Grafana Labs CEO Raj Dutt, Flybridge, IBM, Salesforce Ventures, and Mango Capital.

NetBox Labs is proud to be an equal opportunity employer. We believe diverse teams build better software, and we welcome applicants of every race, color, religion, gender identity, sexual orientation, national origin, age, disability, and veteran status. If you need accommodation at any point in the process, just let us know.