AI Process Forward Deployed Engineer

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: - Deploy and prove: own the end-to-end journey from first process file to a running, measurably improving 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. - Feed the product: You're building the product as you work with customers; this includes features, agents, and skill files. When you find a bug, you're empowered to fix it. - Drive organisational adoption: work across technical and business stakeholders to turn early deployments into lasting customer capability - Work at technical depth: configure Camunda clusters, debug integration failures, and build custom agents where platform defaults don’t fit - Build the playbook: document what good looks like as you discover it and make the next deployment faster - Hand off deliberately: leave each customer team trained, independent, and able to act on improvement results without you What You Bring: - Enterprise production experience: you’ve shipped something inside a large organisation 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 - Ability and/or willingness to use our product 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.

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