
51 - 200 employees
Founded 2012
🏭 Manufacturing
📦 Logistics
💼 Consulting
💰 Venture Round - HiveMQ on 2025-01
Manufacturing • Logistics • Consulting
HiveMQ is a software company that provides an MQTT-based real-time data platform to stream, contextualize, govern, and act on operational telemetry from edge devices to enterprise systems. Its product portfolio includes a cloud-managed offering (HiveMQ Cloud), a self-managed MQTT broker, edge gateways, data hub and analytics tooling to enable always-on, mission-critical IoT and industrial workloads. HiveMQ primarily serves enterprise customers in manufacturing, energy, data centers, transportation and other industries, enabling B2B SaaS deployments that feed AI and analytics workflows with trusted, real-time data.
🕒 June 19
🌐 Germany, United Kingdom, +1 more countries – Remote
💵 €58k - €110k / year
⏰ Full Time
🟠 Senior
☁️ Cloud Engineer
👻 Ghost score 4%
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51 - 200 employees
Founded 2012
🏭 Manufacturing
📦 Logistics
💼 Consulting
💰 Venture Round - HiveMQ on 2025-01
Manufacturing • Logistics • Consulting
HiveMQ is a software company that provides an MQTT-based real-time data platform to stream, contextualize, govern, and act on operational telemetry from edge devices to enterprise systems. Its product portfolio includes a cloud-managed offering (HiveMQ Cloud), a self-managed MQTT broker, edge gateways, data hub and analytics tooling to enable always-on, mission-critical IoT and industrial workloads. HiveMQ primarily serves enterprise customers in manufacturing, energy, data centers, transportation and other industries, enabling B2B SaaS deployments that feed AI and analytics workflows with trusted, real-time data.
• Design and evolve the architecture of our autonomous agent swarm — defining agent boundaries, data flows, and the feedback loops that allow bees to self-correct and deliver features end-to-end. • Build and own the infrastructure that powers our AI-native pipeline, including several AWS services like Lambda functions, DynamoDB, SNS/SQS. • Lead with rigorous technical specs — if the logic isn't in the spec, it doesn't exist — translating complex product requirements into precise, agentic-ready designs that serve as the single source of truth for AI-powered implementation. • Steer and evaluate coding agents and LLM models, reviewing their output against a high-quality mental model to ensure correctness, performance, and security. • Extend and maintain our TypeScript/Fastify backend and React micro-frontend architecture, improving observability, reliability, and test coverage across the stack. • Define and enforce guardrails, monitoring systems, and self-healing mechanisms that keep autonomous agents operating safely in production. • Collaborate with Engineering and Product leadership to shape the long-term vision of AI-native development at HiveMQ. • Stay at the forefront of AI tooling, agent frameworks, and LLM capabilities, continuously refining how the hive thinks and builds.
• A strong software engineering background (5+ years) with hands-on experience architecting and delivering fullstack applications in TypeScript, Node.js, and React. • Production-level experience with AWS infrastructure — Lambda, DynamoDB, and related services — including an intuitive understanding of where things break at scale. • Worked extensively with AI coding agents and LLM-powered workflows, and know how to steer them effectively rather than just prompt them. • A DevOps-first mindset — you've built the monitoring, alerting, and self-healing systems that keep production environments healthy without constant human intervention. • Solid architectural skills around bounded contexts, idempotent design, decoupled micro-frontends, and distributed systems. • The ability to translate ambiguous product goals into precise, agentic-ready technical specs with no room for misinterpretation. • A high sense of ownership and agency — you proactively identify bottlenecks, propose solutions, and follow through without being prompted. • Excellent English communication skills and the ability to collaborate effectively across engineering, product, and leadership in a remote-first environment.
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