Lead Specialist, AI Scientist

About the Role

What You'll Do

• Lead production AI capabilities supporting learner intelligence, personalization, recommendations, knowledge graphs, and AI-powered learning experiences.
• Design and deliver Generative AI, LLM, RAG, and agentic AI solutions with measurable product and business impact.
• Build reusable AI platform capabilities, services, APIs, and workflows.
• Own the AI delivery lifecycle from experimentation through deployment, monitoring, evaluation, and improvement.
• Establish MLOps and AIOps practices for training, deployment, observability, governance, reliability, and operations.
• Partner with Product, Engineering, Design, Learning Science, and Data Science teams.
• Evaluate emerging technologies and architectures while balancing quality, safety, scalability, latency, and cost.
• Establish practices for responsible AI, model evaluation, prompt engineering, agent evaluation, and governance.
• Mentor engineers and data scientists and communicate technical strategy and outcomes to stakeholders.

Expected Results

Qualifications

• Five or more years of experience building and deploying production AI/ML systems, cloud-native applications, and MLOps practices.
• Strong experience with applied machine learning, Generative AI, LLMs, RAG, recommendation systems, knowledge graphs, or agentic AI.
• Hands-on experience with foundation models and modern AI frameworks.
• Proficiency in Python, APIs, testing, CI/CD, version control, and production operations.
• Experience designing scalable AI platforms and deployment architectures in AWS or similar cloud environments.
• Experience with containerization, orchestration, infrastructure as code, and production-grade deployment.
• Experience evaluating and optimizing AI systems for quality, reliability, safety, latency, scalability, and cost.
• Experience with modern AI platforms or frameworks such as OpenAI, Anthropic, Bedrock, Azure OpenAI, LangGraph, LangChain, or Semantic Kernel.
• Strong collaboration and communication skills.
• Bachelor's degree in a relevant field or equivalent practical experience.

Preferred Qualifications

• Master's degree or PhD in computer science, artificial intelligence, machine learning, statistics, or a related discipline.
• Experience in educational technology, personalized learning, assessment, learning science, or related domains.
• Familiarity with psychometrics, proficiency modeling, Bayesian methods, item response theory, or educational measurement.
• Enterprise-scale AI platforms, knowledge graph solutions, or agentic systems experience.
• Contributions to research, patents, open-source projects, or industry thought leadership.

Compensation

• The minimum full-time salary range is listed as $150,000 to $190,000.
• The position is eligible to participate in an annual incentive program.

Workplace

• The location is listed as remote in the United States.
• The posting also lists the workplace type as hybrid.

Schedule

• The schedule is listed as full time.