[All remote jobs](https://jobicy.com/jobs.md)[![NetBox Labs logo](https://jobicy.com/data/server-nyc0409/galaxy/mercury/2025/06/df239a55-221.png)](https://jobicy.com/company/netbox-labs.md)[NetBox Labs](https://jobicy.com/company/netbox-labs.md) # Senior Full Stack Engineer, Observability Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move. [Apply for this job](#job-application)[View company](https://jobicy.com/company/netbox-labs.md)ShareRemote from[UK](https://jobicy.com/job-region/uk.md), [USA](https://jobicy.com/job-region/usa.md), [LATAM](https://jobicy.com/job-region/latam.md)SalaryUSD 85k–98k / yrDepartment[Software Engineering](https://jobicy.com/categories/engineering.md)EmploymentFull TimeExperienceSeniorPublished5 Oct 2026Apply before4 Nov 2026Listing views43Application actions2Application toolkit ## Make your next move. Prepare your resume, explore your fit, and draft a cover letter for this opportunity. AI Summary ## The role, at a glance. NetBox Labs is hiring a senior full-stack engineer for its Observability team to build network discovery, assurance, fleet-management, and telemetry products. The role spans Go and Python backend services, gRPC and REST APIs, ingestion pipelines, and React/TypeScript monitoring dashboards. The engineer will own features end to end, operate production services, join on-call, and improve performance and reliability for large network environments. Strong experience with distributed systems, real-time data visualization, automated testing, and cross-functional collaboration is required. Networking, network telemetry, NetBox, and AI-enabled development workflow experience are valuable differentiators. ## Role DNA A quick view of the complexity, pace, ownership and collaboration implied by the job description. ### Job Complexity 5/5EasyHard ### Pace & Pressure 4/5RelaxedFast-paced ### Autonomy Level 5/5GuidedFull ownership ### Communication Load 4/5IndependentCollaborative AI insightThis is a senior, end-to-end engineering role requiring production depth across backend distributed systems, API design, frontend telemetry visualization, and service operations. It also calls for architectural judgment, mentoring, on-call ownership, and performance work at large-scale telemetry volumes. ## Salary analysis Estimated compensation compared with the broader US market for similar roles. Estimated job medianBelow market$91,500US market range$140k–$190k0$209k AI insightThe disclosed annual salary range is USD 85,000–98,000, producing a job-offer median of USD 91,500. For a US-based senior full-stack observability engineer with Go, Python, React, distributed systems, and on-call responsibilities, an estimated US market base-salary range is USD 140,000–190,000 annually; actual compensation varies by location, company stage, and equity or bonus structure. ## Core skills Skills and capabilities most closely associated with this opportunity. [Go](https://jobicy.com/jobs?search_keywords=Go.md)[Python](https://jobicy.com/jobs?search_keywords=Python.md)[React](https://jobicy.com/jobs?search_keywords=React.md)[TypeScript](https://jobicy.com/jobs?search_keywords=TypeScript.md)[gRPC](https://jobicy.com/jobs?search_keywords=gRPC.md)[REST APIs](https://jobicy.com/jobs?search_keywords=REST%20APIs.md)[Distributed Systems](https://jobicy.com/jobs?search_keywords=Distributed%20Systems.md)[Telemetry Dashboards](https://jobicy.com/jobs?search_keywords=Telemetry%20Dashboards.md)[Network Observability](https://jobicy.com/jobs?search_keywords=Network%20Observability.md)[Kafka/RabbitMQ](https://jobicy.com/jobs?search_keywords=KafkaRabbitMQ.md) Sample interview questionsHow would you design a telemetry ingestion path that remains reliable when agents reconnect and resend data?I would use durable message delivery, idempotency keys or deterministic event identifiers, and storage-level deduplication where appropriate. The pipeline should acknowledge data only after durable processing, implement retry and backoff behavior, expose lag and failure metrics, and define clear ordering and late-data semantics. What considerations matter when evolving a gRPC API used by agents and web clients? I would preserve backward compatibility by following Protocol Buffers evolution rules, avoiding reuse of field numbers, and making new fields optional or safely defaulted. I would also version behavior deliberately, define deadlines and structured errors, test compatibility between versions, and document migration expectations for consumers. How would you keep a React telemetry dashboard responsive with high-frequency, high-cardinality data? I would constrain queries by time range and resolution, aggregate or downsample on the server where possible, and use client-side virtualization for large lists. For charts, I would choose performant rendering such as canvas or WebGL when needed, cache query results, throttle live updates, and avoid unnecessary React re-renders through memoization and well-scoped state. Describe how you would investigate a production incident involving delayed device discovery data. I would first assess impact and inspect end-to-end latency metrics across agents, queues, ingestion services, and persistence layers. I would correlate logs and traces using a device or job identifier, check queue depth, error rates, saturation, and recent deployments, then mitigate the bottleneck while communicating status clearly. After recovery, I would document root cause and implement preventive monitoring, tests, or capacity changes. How do you use AI coding assistants safely in an engineering workflow? I use them to accelerate drafting, refactoring, test generation, and documentation, but treat output as untrusted until reviewed and validated. I keep prompts free of sensitive customer data and credentials, request small reviewable changes, verify behavior with tests and static analysis, and ensure architectural and security decisions remain grounded in the codebase and team standards. Opportunity details ## About this role. 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: * NetBox Discovery finds devices, interfaces, and other network entities. * NetBox Assurance brings discovered data into NetBox and helps operators spot drift between intended and actual state, review changes, and decide what to accept. * 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. * 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: * 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. 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 * 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. What we’re looking for (minimum 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. ### About NetBox Labs: 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, and 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. ### Our culture and values: * We own and solve problems with high attention to detail. * Our open source contributors, users, customers & team are all part of our community. When our community wins, we win. * We prioritize simplicity and think twice before adding complexity * Clear communication helps keep our team aligned and collaborating smoothly. 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. 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