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.
Requirements
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 practical knowledge of LLM application architecture, including retrieval (RAG), grounding, prompt/system design, and structured outputs.
Experience implementing evaluation and reliability loops (test harnesses, offline/online evals, monitoring, feedback, iteration) and guardrails (safety, policy, data controls).
Proven ability to integrate agentic workflows with enterprise systems and data (APIs, events, identity, governance) and to design complex integration architectures.
Strong background in system architecture and end-to-end solution delivery (security, scalability, reliability, observability, deployment readiness).
Experience with enterprise platforms and ecosystems (Siemens stack a plus), data platforms, and modern AI tooling.
Ability to translate complex technical capabilities into reusable patterns, reference architectures, and clear technical narratives for GTM and customer contexts.
Strong communication and collaboration skills across Product, GTM, engineering, and customer stakeholders.