Principal AI Engineer, Wolters Kluwer

• A Bachelor’s, Master’s, or Ph.D. degree in Computer Science, Artificial Intelligence, or a related field, or equivalent professional experience
• Proven track record of delivering Generative AI applications to production in customer-facing products
• Expertise in agent-based AI frameworks (e.g., LangGraph, Semantic Kernel, LangChain, or equivalents)
• Strong background in production-grade software engineering, with proficiency in Python and cloud-native development
• Experience with hyper-scaler AI services (AWS, Azure, Google Cloud) and their ecosystem of AI/ML tools
• Expertise in AI model evaluation, fine-tuning, cost optimization, and observability
• Experience with MLOps, CI/CD for ML and software

Desirable

• The Principal AI Engineer will be a key contributor to the design, development, and delivery of advanced Generative AI applications in customer-facing products. This role requires expertise in agent-based AI frameworks, as well as strong proficiency in evaluation, tuning, scaling, and cost management of production AI systems
• Working closely with the AI Platform team, the Principal AI Engineer will develop advanced AI capabilities into the company’s platform, enabling scalable adoption across the product portfolio. The engineer will champion best practices in quality, safety, observability, and performance, ensuring that AI solutions deliver measurable business value
• This is a highly collaborative role that combines technical leadership, production-grade software engineering, and cross-functional engagement to accelerate the adoption of operational AI solutions
• Design and deliver production-ready AI solutions, with a focus on generative AI and agent-based applications
• Optimize and scale AI systems for latency, throughput, cost efficiency, and reliability
• Lead efforts on fine-tuning, evaluation, and monitoring of models in real-world environments
• Implement observability frameworks for ongoing quality and safety validation of deployed models
• Collaborate with the AI Platform team to expand AI components and services into the enterprise AI platform
• Drive platform improvements that enable scalable adoption of generative AI across multiple products
• Establish design patterns, architecture standards, and frameworks for building AI-powered solutions
• Define and enforce best practices for responsible AI, covering quality, safety, fairness, and compliance supporting AI Governance
• Champion techniques for evaluation, benchmarking, and model lifecycle management
• Ensure secure, compliant, and cost-effective use of hyper-scaler AI services and cloud infrastructure
• Mentor and guide AI engineers and product teams on technical approaches and implementation
• Partner with platform and product engineering, product owners, subject matter experts, and operations teams to ensure delivery of AI solutions
• Engage with external AI technology providers to leverage state-of-the-art advancements