AI Platform & Agentic Architect
Role details
Job location
Tech stack
Job description
As an AI Platform & Agentic Architect you design the shared AI platform every use case runs through: a model gateway, an agentic architecture, and guardrails and sovereignty built in from the start. Build it once, make it reusable, keep it safe and vendor-neutral., * Own and evolve the reference architecture for our AI platform, including the model garden, a governed model gateway providing unified access to all models, and the orchestration of AI agents.
- Define enterprise standards for agentic AI, covering approved agent frameworks (commercial and open source), MCP-based integrations, multi-agent coordination patterns, and scalable agent memory architectures.
- Set standards for agent evaluation, reliability and observability, so agents are dependable in production, not just in demos.
- Design the gateway for reuse, control, audit, provider-independence and cost/token transparency.
- Build governance, security, and digital sovereignty into the AI platform, including EU AI Act compliance evidence and audit logging, guardrails, data residency controls, customer-managed encryption keys, and a comprehensive agent control plane covering machine identities, agent registration, and release governance.
- Define the paved-road patterns and sandbox-to-production paths that let teams move from idea to value in weeks., * Close collaboration in a motivated team with an open feedback culture that promotes your personal and professional development.
- Insights into a global energy company.
- Hybrid working and flexible working time models.
- Free access to the Health Center, modern open workspaces, free parking, e-charging stations and much more.
- Structured and digitized pre- and onboarding process supported by the web-based app RWE+You.
Requirements
- University degree (or equivalent) in Computer Science, Computer Engineering, or Information Technology or related field.
- Several years of hands-on working experience in AI platform architecture and agentic AI in a regulated decentral environment.
- Deep experience in designing and running AI/ML or GenAI platforms at scale.
- Strong agentic AI expertise: agent orchestration and multi-agent frameworks (e.g. Copilot Studio, Databricks, LangGraph, Semantic Kernel, AutoGen), MCP, tool use, memory and human-in-the-loop patterns.
- Solid knowledge of cloud architecture (Azure and AWS), containers, and API/gateway design.
- Experience with LLMOps and AgentOps: model and agent evaluation, guardrails, tracing and CI/CD.
- Working knowledge of EU AI Act, identity and access (including machine identities) and data-sovereignty concepts.
- A strong bias for reusable, standardised platforms over bespoke builds.
RWE is committed to creating a diverse and inclusive environment - we value your passion, your willingness to learn and your desire to thrive. Even if you don't have all of the above skills , but think the job would be a good fit for you, you need flexible working arrangements or we need to make adjustments not yet listed here, we'd love to hear from you.