Principal AI Engineer

RWE Americas, LLC

To start as soon as possible, full time, permanent

Functional area: IT / Digital

Remuneration: Exempt

The Principal AI Engineer is a platform level technical expert responsible for building and operating the shared AI capabilities that squads and business units build on, and for setting the engineering patterns and reference implementations that other engineers follow. This role owns the technical design, build, and operational decisions for those shared capabilities, working within the platform roadmap set by the head of AI Platform and Products, and the target-state architecture set by the Data/AI Platform Architect.

This role integrates and operates shared platform services including orchestration and agent frameworks, retrieval and knowledge services, evaluation tooling, model and prompt lifecycle management, observability, and guardrails.

The Principal AI Engineer operationalizes responsible AI at the platform level, delivers AI platform cost efficiency, and raises the output of the wider AI organization.

• Integrate and operate the shared AI platform capabilities squads and business units build on, including orchestration and agent frameworks, retrieval and knowledge services, evaluation tooling, model and prompt lifecycle management, observability, and guardrails. Ensure they are production-ready, supportable, and adopted across squads consistent with the enterprise target-state architecture and platform roadmap
• Solve the enterprise’s hardest AI engineering problems, including retrieval quality against a fragmented document and operational data estate, building useful models where labeled outcomes are scarce, enabling agents to operate safely in compliance-bound workflows, and resolving assets, sites, and other entities across systems with no common identifiers
• Define reference implementations for AI development across squads and drive their adoption, making the engineering standard visible, consistent, and teachable
• Operationalize responsible AI at the platform level through evaluation and guardrail infrastructure, explainability and citation, bias and drift detection, override and audit logging, prompt and model versioning, and the evidence trail required for compliance and audit
• Deliver AI platform cost efficiency through instrumentation and per-product economics, leading structural changes across routing, caching, context management, and model tiering that keep spend proportional to the value delivered, within the enterprise AI Fin Ops framework
• Multiply the output of the engineering organization by leading design reviews, coaching senior engineers, and evolving platform standards

• Master’s or PhD degree in computer science, data science, STEM, or related field required
• Minimum 11 years of relevant professional experience in software or AI/ML engineering roles, including demonstrated experience building and operating shared platform capabilities used by multiple engineering teams and setting technical patterns that other engineers follow
• Deep expertise in enterprise-scale AI development, with the ability to set engineering standards that other engineers follow within an established platform architecture
• Production experience with a major cloud platform, Python, containerized deployment and CI/CD for AI services, and current LLM orchestration and agent frameworks
• Extensive experience integrating and operating the shared AI platform services described above in a production enterprise environment, with personal accountability for their reliability and supportability
• Depth in responsible AI engineering, with hands‑on ownership of the evaluation, guardrail, and audit infrastructure described above
• Demonstrated ability to drive AI platform cost efficiency using the structural levers described above
• Proven ability to mentor and professionally develop junior AI engineers
• Experience with IT/OT environments, industrial data sources, or operational technology systems preferred
• Experience in the power, utilities, or clean energy sector, including knowledge of U.S. power markets, renewable project development, and clean energy technologies…