ГерманияForward Deployed Engineer, DACH
1 мес. назад
ГерманияOnsite
Embed with enterprise customers to architect and deploy production systems on 's global network.
О компании
- is an industry leader that's not just imagining the future of global connectivity—we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network , to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications.
- We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team.
- Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers.
Обязанности
- We're building a local Enterprise Sales Pod in Munich — one AE and one Forward Deployed Engineer (FDE), working together to build a enterprise business in your market. You'll embed directly with enterprise customers to architect and ship production systems on 's global network — voice, messaging, AI, and wireless. This isn't about demoing products. It's about building real solutions that work at scale. You'll work side-by-side with a dedicated Enterprise AE — not a demo resource, but a commercial partner who owns the named-account list, builds executive relationships, and closes the deal. You own the technical side: discovery, architecture, POC, and production go-live. You win together. No throw-over-the-wall. The Pod Model Enterprise AE — owns the named-account list, builds executive relationships, gets in the room, owns commercial qualification and close, expands the account. . Forward Deployed Engineer — owns technical discovery, designs the architecture, builds the POC when gated, gets the first workload live, removes blockers and finds the next workload. We sell the workload, not the SKU. Customers buy a production outcome — an AI contact center, a SOC/NOC agent, global communications, connected mobility, or enterprise inference — that runs on primitives (voice, messaging, numbers, wireless, Voice AI, inference, agents, connectivity). You lead with the outcome conversation, not a product menu. What You'll Do • Embed with enterprise customers to unders
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- • Troubleshoot and resolve complex integration issues alongside customer teams What We're Looking For • CS degree or equivalent experience • 3+ years building and shipping production software — you've written code that real users depended on, you've been on-call for it, and you've debugged it when things broke. (A consulting background counts if this is also true of you.) • Proficiency in multiple languages: Python, Node.js/TypeScript, Go — you're more dangerous in some than others. ( Edge Compute — functions and stateful actors — is TypeScript, so that one pulls double duty.) • Practical understanding of what breaks in front of a model in production: provider rate limits and quotas, timeout and retry behavior, streaming, token accounting and cost attribution, and the failure modes that only show up under concurrency • Comfortable deploying containerized services on Kubernetes, with secrets management, config, and upgrades as part of the deployment story • You've wired observability and been paged because of it — Prometheus + Grafana, OpenTelemetry, Graylog, ELK, or equivalent. You know what to monitor, what to alert on, and what "healthy" looks like • High-concurrency experience — Kafka, message queues, or event streams at real scale. When throughput spikes you know what breaks — consumer lag, backpressure, hot partitions, rebalance stalls — and what absorbs it: partitioning, consumer groups, parallelism up to your partition count • You've built APIs from scratch, not
Другое
- #LI-RH1