Senior AI Engineer

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Camunda is the leader in enterprise agentic automation, orchestrating complex business processes, including high-value knowledge work, across agents, people, and systems. By creating production-ready, enterprise-grade agents with built-in governance, Camunda uniquely delivers trusted AI agents for business-critical processes. Over 700 leading innovators like Atlassian, ING, and Vodafone, rely on Camunda to slash time-to-value from months to days, boost operational efficiency, and elevate customer experiences. Camunda was named a Visionary in the inaugural 2025 Gartner® Magic Quadrant™ for Business Orchestration and Automation Technologies (BOAT).

As a fully remote, global company, we’re rewriting the rules of modern business. Named GP Bullhound’s 2024 Top 100 Next Unicorn list, certified as a Great Place to Work, and recognized by Flexa for true flexibility, we’re growing fast and looking for top talent to join our team. If you’re excited to do meaningful work and make real impact, keep reading, this role could be the one you’ve been waiting for.

About The Role

We’re entering a new era of automation, where Agentic AI can automate manual work like never before. At Camunda, we’re building the operating system for this future.

Our Enterprise Agentic Automation Team (EAAT) designs and operates production-grade agentic solutions that automate critical business processes at Camunda while serving as credible proof points for our customers.

As a Senior Engineer in our Enterprise Agentic Automation Team, you will design, build, and operate enterprise-grade agentic AI systems embedded in Camunda-orchestrated workflows. You will turn AI capabilities into reliable, secure, and scalable production systems that run at the core of our organization.

What You Will Do

• Design and implement production-grade agentic orchestration systems combining executable BPMN, Camunda workers/connectors, DMN, and AI components • Design and build AI agents with clearly defined responsibilities, tools, memory strategies, and decision boundaries • Engineer and govern context pipelines (static instructions, dynamic enrichment, RAG, constraints, evaluation signals) to ensure reliable model behavior • Implement structured prompting, output enforcement, human-in-the-loop patterns, and guardrails for safe, controllable execution • Build evaluation frameworks, feedback loops, and testing for deterministic and non-deterministic systems • Operate agents in production (AgentOps): logging, monitoring, alerting, incident response, and continuous improvement • Contribute to production infrastructure standards including CI/CD, environment separation, secrets management, and security fundamentals

Must Haves

What You Will Bring to the Role:

• 5+ years experience designing, building, and operating production-grade systems (backend, platform, or full-stack) with Java/Spring, including scalable services, integrations, and APIs. • Proven AI Engineering experience building, testing and operating LLM-powered systems in production • Hands-on experience with agent frameworks such as LangChain, LangGraph, CrewAI, or similar • Practical experience with context engineering (RAG pipelines, retrieval strategies, structured outputs, evaluation signals) • Demonstrated end-to-end ownership across design, implementation, deployment, and operations • Solid understanding of cloud-native infrastructure and production operations (CI/CD, environment separation, secrets, monitoring, incident response)

Nice To Haves

• Experience with Camunda, BPMN, DMN, or other workflow/orchestration platforms • Experience building reusable internal platforms, shared services, or developer enablement components • Experience work