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Principal Product Software Engineer | AI Engineer

Wolters Kluwer
Full-time
On-site
Princeton
**This is a Hybrid role requiring 2 days a week in a Wolters Kluwer office** 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. Key Responsibilities: AI Solution Delivery 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. Platform & Architecture Contributions 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. Best Practices & Governance 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. Leadership & Collaboration 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. Qualifications: Required Skills & Experience 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 Preferred Skills Knowledge of

model safety, interpretability, and alignment techniques . Experience with

multi-agent orchestration

and advanced reasoning systems. Familiarity with

compliance, privacy, and governance frameworks

in AI applications. Strong communication skills to

influence technical and non-technical stakeholders . Benefits:

A comprehensive benefits package that begins your first day of employment.