Principal AI Engineer

At RWE Americas, you will help shape shared, production-grade AI capabilities that support multiple squads and business units across the enterprise. This principal platform role combines technical leadership with hands-on ownership across orchestration, retrieval and knowledge services, evaluation, model and prompt lifecycle management, observability, and guardrails. You will also operationalize responsible AI and drive cost efficiency through instrumentation and AI FinOps principles.

Location: Chicago, IL (onsite). Additional office-based travel and visits to other RWE Americas offices and field locations are required. The position is office-based with some travel, and you must be able to sit, walk, or stand for long durations of time. Pay: USD 178,000 - 240,000 per year base salary range in Illinois. Remuneration: Exempt.

What you’ll do

• Integrate and operate shared AI platform capabilities used by squads and business units, including orchestration and agent frameworks, retrieval and knowledge services, evaluation tooling, model and prompt lifecycle management, observability, and guardrails, ensuring production readiness, supportability, and adoption aligned to the enterprise target-state architecture and platform roadmap.
• Tackle enterprise-scale AI engineering challenges such as improving retrieval quality across fragmented document and operational data estates, building useful models when labeled outcomes are scarce, enabling agents to operate safely in compliance-bound workflows, and resolving assets, sites, and other entities across systems without common identifiers.
• Define reference implementations for AI development across squads and promote adoption by making engineering standards 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 needed for compliance and audit.
• Drive AI platform cost efficiency by instrumenting usage and per-product economics, leading structural changes across routing, caching, context management, and model tiering to keep spend proportional to value delivered within the enterprise AI FinOps framework.
• Multiply impact through design reviews, coaching senior engineers, and evolving platform standards.

What you bring

• Master’s or PhD degree in computer science, data science, STEM, or a related field.
• Minimum 11 years of relevant professional experience in software or AI/ML engineering, including demonstrated experience building and operating shared platform capabilities used by multiple engineering teams and setting technical patterns others follow.
• Deep expertise in enterprise-scale AI development, with the ability to set engineering standards within an established platform architecture that other engineers follow.
• Production experience on a major cloud platform, including Python, containerized deployment, and CI/CD for AI services, along with current LLM orchestration and agent frameworks.
• Extensive experience integrating and operating shared AI platform services in a production enterprise environment with personal accountability for reliability and supportability.
• Hands-on depth in responsible AI engineering, including ownership of evaluation, guardrail, and audit infrastructure.
• Demonstrated ability to drive AI platform cost efficiency using structural levers such as routing, caching, context management, and model tiering.
• Proven ability to mentor and professionally develop junior AI engineers.
• Preferred: 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.
• Must be legally authorized to work in the United States; RWE Americas is unable to sponsor or take over sponsorship of employment visas at this time.

Tools you’ll use

• Python
• CI/CD
• LLM orchestration
• Agent frameworks
• Containerized deployment

Benefits

• Medical, Dental, Vision
• Life Insurance
• Short-Term Disability, Long-Term Disability
• 401(k) match
• Flexible Spending Accounts
• EAP
• Education Assistance
• Parental Leave
• Paid time off
• Holidays
• Eligible employees also participate in short-term incentives, in addition to salary