Forward Deployed Engineer

Camunda is the enterprise platform for agentic orchestration, enabling organizations to coordinate AI agents, people, and systems across complex, end-to-end business processes. With built-in governance, auditability, and human oversight, Camunda gives enterprises the control they need to move AI from pilots to production — safely and at scale. Trusted by over 700 organizations worldwide, including 9 of top 10 US banks, Camunda helps enterprises boost operational efficiency, accelerate time-to-value, and deliver better customer experiences. Fully remote and global, we are in the middle of something bigger: transforming into an AI-first organisation, built on our own platform. We use Agentic AI to automate, orchestrate intelligent processes, and elevate human contribution across every team. Named GP Bullhound’s Top 100 Next Unicorn list, 2025 Great Place to Work certified. Visionary in 2025 Gartner® Magic Quadrant™ for Business Orchestration and Automation Technologies. ranked 3rd in Flexa's 2026 Most Flexible Companies, We’re growing fast and looking for top talent to join our team. If you want meaningful work, visible impact and put something genuinely rare on your CV, keep reading. About the role: As an AI Forward Deployed ProcessOS is a new kind of Camunda product: business processes described in natural language, generated as executable BPMN workflows, and improved autonomously from production data. We’re hiring the first cohort of Forward Deployed Engineers to bring it into production at enterprise customers. You’ll own the deployment journey from first process file to a working, improving system, and hand off a functioning capability to the customer’s team. The code you write and the patterns you discover feed directly back into how ProcessOS is built. This is a rare opportunity to shape a product, a function, and a field practice from day one. You’ll work end‑to‑end across Java services and React interfaces, collaborating closely with a talented global team to measure, improve, and scale performance and fault tolerance in real-world distributed systems. What You’ll Be Doing: - Ability and/or willingness to use our product - Deploy and prove. Own the journey from first process file to production workflow. At 90 days: at least one workflow running, the improvement loop active, and measurable fitness gains the customer can see. At 12 months: 3–5 customers with viable deployments. - Drive organizational adoption. Work across technical and business stakeholders to build understanding and trust, turning early deployments into lasting customer capability. - Work at depth technically. Configure and run Camunda clusters locally and in cloud environments. Debug integration failures. Build custom agents where platform defaults don’t fit. Write connector logic that gets legacy enterprise systems talking to ProcessOS. - Build the playbook. There is no deployment template yet. Document what good looks like as you discover it, and make the next implementation faster. - Feed the product. Custom integrations you write get contributed back. Integration patterns get codified. Production bugs you find, you often fix. Your field work is a direct input to ProcessOS. - Hand off deliberately. Leave customers with a team that can operate independently, is trained on the platform, and acts on improvement results without you. Must Haves: - Enterprise production experience: you’ve shipped something inside a large organization and stayed to see it operate. You know why governance and resilience matter at scale. - Technical depth: You can debug an integration failure, write a custom agent against a legacy API, stand up a Camunda cluster from scratch, and explain generated BPMN to both engineers and business leads. - Stakeholder communication: you work effectively across engineering, architecture, and business leadership and adapt how you communicate without losing precision. - Practical AI experience: you’ve used AI to solve real problems in production – not just experimented. You understand context management, prompt engineering, agent testing, and integration tradeoffs. - Comfort with ambiguity: you make sound judgment calls without a playbook and document what you learn. - Occasional travel may be required Nice to Haves: - Experience in a customer-facing engineering or professional services role. - Familiarity with regulated industries such as financial services, healthcare, or insurance - Production experience with agentic systems or AI-integrated workflows. - Contributions to a shared platform or open source project that others built on.