AI/ML Engineer - Higher Ed
Role details
Job location
Tech stack
Job description
HED AI Feature Development
- Ship and improve AI features weekly across Cengage HED platforms
- Build and integrate Student Assistant capabilities including tutoring, hinting, and feedback
- Develop Instructor Insight Assistant features for course analytics and at-risk student identification
- Create Content Studio capabilities for AI-assisted content authoring and adaptation
- Integrate LLMs, RAG systems, and agentic workflows into HED platform architectures
Platform Integration & Engineering
- Integrate AI features into existing HED platform architectures and data systems
- Partner with platform engineering on API design, scaling, and production deployment
- Build retrieval systems against Cengage's proprietary content library (books, assessments, media)
- Ensure AI features meet FERPA compliance and accessibility standards (WCAG, DOJ)
- Resolve technical blockers and production issues with urgency
Measurement & Optimization
- Monitor feature usage, engagement, and learning outcome impact
- Track and improve model performance on quality, cost, and latency dimensions
- Partner with learning scientists and researchers on efficacy measurement
- Iterate rapidly based on student feedback, instructor feedback, and usage telemetry
- Maintain documentation and engineering runbooks for deployed AI features, * Languages: Python, JavaScript/TypeScript, SQL
- AI/ML: OpenAI API, Anthropic API, AWS Bedrock, LangChain, LlamaIndex, Hugging Face
- Vector DBs: Pinecone, Weaviate, pgvector, Chroma
- Cloud: AWS (Lambda, ECS, SageMaker, Bedrock), Azure OpenAI
- Data: Snowflake, Databricks, Postgres, Redis
- DevOps: Docker, Terraform, GitHub Actions, CI/CD pipelines
Key Competencies
- Shipping Mindset - delivers features weekly, not quarterly
- Technical Craft - writes clean, tested, production-grade code
- Learning Orientation - cares about whether AI actually improves learning outcomes
- Systems Thinking - sees the full platform and integrates AI cleanly
- Collaboration - partners effectively with product, design, research, and platform engineering
- Continuous Improvement - iterates on models and features based on data
What We Offer
- Opportunity to shape AI at scale across a global learning company
- Direct impact on business outcomes, product, and workforce productivity
- Access to cutting-edge AI tools, platforms, and technologies
- Collaborative team environment focused on innovation and continuous improvement, The Engagement Manager leads onboarding and activation for enterprise accounts, presenting to senior leadership and creating repeatable frameworks to enhance engagement. This role requires driving execution and managing the full lifecycle of client interactions, focusing on achieving clear outcomes and customer satisfaction.
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field
- 4+ years of experience in software engineering, with at least 2 years focused on AI/ML
- Strong proficiency in Python with experience building production ML or LLM systems
- Hands-on experience with modern AI APIs (OpenAI, Anthropic, AWS Bedrock)
- Experience with RAG architectures, vector databases, and embedding models
- Solid software engineering fundamentals including testing, CI/CD, and system design
- Experience shipping production features at scale (thousands or millions of users)
- Strong communication skills to work with product, design, and research partners, * Experience in EdTech or adjacent domains with production education AI features
- Familiarity with agentic AI frameworks (LangChain, LlamaIndex, CrewAI)
- Background in learning science, educational psychology, or instructional design
- Experience with FERPA compliance and education-industry data handling
- Familiarity with accessibility standards (WCAG, Section 508, DOJ accessibility)
- Experience with fine-tuning, LoRA, or custom model training
Benefits & conditions
At Cengage Group, we take great pride in our commitment to providing a comprehensive and rewarding Total Rewards package designed to support and empower our employees. Click here to learn more about our Total Rewards Philosophy.
The full base pay range has been provided for this position. Individual base pay will vary based on work schedule, qualifications, experience, internal equity, and geographic location. Sales roles often incorporate a significant incentive compensation program beyond this base pay range.
In this position, you will be eligible to participate in the company's discretionary incentive bonus program. This position's bonus target amount, which is not guaranteed and is dependent on individual performance and overall company results among other factors, is provided below.
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Engagement Manager
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