Lead Specialist, AI Scientist

Lead Specialist, AI Scientist Location: Remote, United States About the Role

We are seeking a strategic and hands-on Lead Specialist- AI Scientist to design, build, deploy, and scale production AI/ML capabilities that power Pearson's learner intelligence, knowledge graphs, recommendations, personalized learning experiences, and next-generation AI products.

This role bridges AI research, data science, software engineering, and product delivery. The successful candidate will lead the development of machine learning, Generative AI, LLM, agentic AI, and knowledge graph solutions, taking them from concept and experimentation through production deployment and continuous improvement. The ideal candidate combines deep technical expertise with a strong execution mindset and a passion for delivering measurable learner and business outcomes.

What You'll Do

• Lead the design, development, deployment, and operation of production AI capabilities supporting learner intelligence, personalization, recommendations, knowledge graphs, and AI-powered learning experiences.

• Design and deliver Generative AI, LLM, retrieval-augmented generation (RAG), and agentic AI solutions that create measurable product and business impact.

• Build reusable AI platform capabilities, services, APIs, and workflows that accelerate AI adoption across Pearson products.

• Own the end-to-end AI delivery lifecycle, from experimentation and prototyping through deployment, monitoring, evaluation, and continuous improvement.

• Establish scalable MLOps and AIOps practices for model training, deployment, observability, governance, reliability, and operational excellence.

• Partner closely with Product, Engineering, Design, Learning Science, and Data Science teams to identify opportunities and deliver impactful AI-powered capabilities.

• Evaluate emerging AI technologies, foundation models, and architectural approaches while balancing quality, safety, scalability, latency, and cost.

• Establish best practices for responsible AI, model evaluation, prompt engineering, agent evaluation, and AI governance.

• Mentor engineers and data scientists and help elevate AI engineering capabilities across the organization.

• Communicate technical strategy, architecture decisions, trade-offs, risks, and outcomes to stakeholders across the business.

Expected Results:

• Production-ready learner intelligence, recommendation, and knowledge graph capabilities powering personalized learning experiences.

• Enterprise-scale AI services, LLM applications, and agentic workflows integrated into Pearson products.

• Reusable AI platform components enabling rapid development, evaluation, deployment, and scaling of AI-powered capabilities.

• Reliable, secure, observable, and cost-efficient AI systems operating successfully in production environments.

• Accelerated transition of AI prototypes and research into measurable product and business outcomes.

• Improved learner engagement, efficacy, productivity, and business impact through deployed AI capabilities.

Qualifications

• 5+ years of experience building and deploying production AI/ML systems, including cloud-native applications and MLOps practices.

• Strong experience with applied machine learning, Generative AI, LLMs, RAG architectures, recommendation systems, knowledge graphs, or agentic AI solutions.

• Hands-on experience building and deploying AI applications using foundation models and modern AI frameworks.

• Proficiency in Python and modern software engineering practices, including APIs, testing, CI/CD, version control, and production operations.

• Experience designing scalable AI platforms, services, and deployment architectures in AWS or similar cloud environments.

• Experience with containerization, orchestration, infrastructure-as-code, and production-grade deployment practices.

• Exper...