The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
The ad says“Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures”
The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
The ad says“Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures”
The ad says“Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures”
The ad says“Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs”
The ad says“Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)”
The ad says“Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)”
The ad says“Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)”
Values
The ad says“Mendix experience is a plus”
Mendix, a Siemens business, powers hybrid agentic workforces by enabling organizations to build, scale and orchestrate agents and applications faster by combining low-code, AI, data, and integrations into a unified platform
The Technical Solutions Marketing team builds technical credibility for Mendix through validated architectures, reusable proof points, and real-world implementations
In this role, you will work directly with customers and the field to prove high-value use cases through lighthouse implementations, then package what works into reusable patterns, components, and technical narratives that scale across GTM and delivery ecosystems
Design and implement customer-facing prototypes and lighthouse implementations to validate high-value AI and integration use cases
Lead strategic workshops and technical deep dives with customers and field teams, especially for agentic AI workflows and complex integrations
Turn validated customer work into reusable assets: reference architectures, blueprints, accelerators, and repeatable patterns
Serve as the deep technical owner for agentic system design, including tool use, orchestration, and multi-agent patterns
Design and maintain complex integration architectures across enterprise platforms and data systems
Ground GTM positioning and storytelling in validated technical proof points, supporting high-impact moments like executive demos and analyst briefings
What Success Looks Like:
Lighthouse customer implementations that prove value, de-risk adoption, and generate validated technical proof points
Packaged assets (patterns, blueprints, components, playbooks) reused across GTM and adopted by Services/partners for repeatable delivery
Reliable, scalable demo and workshop environments that consistently showcase complex AI/data/integration scenarios
A strong feedback loop into Product and PMM informed by real customer builds
This role sits at the intersection of deep technical work and real business impact, and plays a central part in how Mendix’s AI and integration capabilities are proven, packaged, and scaled
You will design and validate the architectures that become the foundation for how customers adopt the platform, how Services delivers at scale, and how GTM tells a credible technical story
Benefits
Work from home opportunities
Family leave
Retirement savings
Commuter Benefits
Generous Paid time off
Outings & Events
Training & Development
Preferred experience
Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls)
Ability to translate complex technical capabilities into reusable patterns, reference architectures, and clear technical narratives for GTM and customer contexts
Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures
Experience with enterprise platforms and ecosystems (Siemens stack a plus), data platforms, and modern AI tooling
Mendix experience is a plus
Demonstrable, hands-on experience designing and building agentic AI systems in production-realistic environments (tool use/function calling, orchestration/planning, multi-agent patterns where appropriate)
Strong communication and collaboration skills across Product, GTM, engineering, and customer stakeholders
Strong practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs
Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness)
