At Cengage, our employees have a direct impact in helping learners around the world discover the power and joy of learning. We are bonded by our shared purpose – driving innovation that helps millions of learners improve their lives and achieve their dreams through education.
AI/ML Engineer – Core AI
The AI/ML Engineer for Core Systems - Core AI team is a high-output, full-stack engineering role aimed at quickly producing fully functional AI-powered application prototypes. This is a hands-on position for a versatile engineer who acts swiftly, codes in multiple languages, and uses AI-assisted development tools to considerably accelerate delivery.
Your role involves turning concepts into functional applications, not simply mock-ups or wireframes. You will build prototypes that prove business value and technical feasibility. The ideal applicant is proficient in modern programming languages and has strong experience working with AWS services. You adopt AI-forward development techniques using tools like Open AI Codex, GitHub Copilot, Claude, and other AI coding assistants. You have engineering-level knowledge of LLMs and core AI/ML concepts and can integrate these technologies into production-ready software.
Key Responsibilities
Rapid Prototype Development
- Produce fully working AI-enhanced application prototypes swiftly-from initial concept to working demonstration in just days
- Develop end-to-end solutions including backend services, APIs, data pipelines, and frontend interfaces
- Transform business requirements and technical concepts into tangible, demonstrable applications
- Iterate rapidly based on feedback, adjusting quickly to refine or redirect prototypes
- Create reusable code libraries, templates, and scaffolding to accelerate future development
- Ensure prototypes are sufficiently robust to support collaborator demos and user testing
- Leverage AI coding assistants (Codex, GitHub Copilot, Claude, Cursor) to improve development speed and quality
- Keep up to date with new AI development tools and incorporate them into everyday workflows
- Use LLMs for code generation, debugging, refactoring, documentation, and test creation
- Develop prompt engineering techniques to optimize AI-assisted coding output
- Contribute to team guidelines for AI-augmented software development
- Assess and suggest new AI development tools and methodologies
- Develop and deploy applications on AWS cloud platforms
- Leverage managed AI/ML services including AWS Bedrock, SageMaker, Agentcore, Stands SDK
- Implement serverless architectures (Lambda, Azure Functions) for rapid, scalable deployments
- Design and build containerized applications using Docker and Kubernetes
- Configure cloud infrastructure using IaC tools (Terraform, CloudFormation, Bicep)
- Optimize for cost, performance, and security in cloud environments
- Integrate LLMs and foundation models into applications with deep understanding of their capabilities and limitations
- Implement RAG (Retrieval-Augmented Generation) architectures, vector databases, and embedding pipelines
- Build prompt engineering solutions, fine-tuning workflows, and model orchestration patterns
- Build agentic AI systems and multi-step reasoning workflows
- Apply core ML principles including model evaluation, inference optimization, and responsible AI practices
- Connect AI capabilities to enterprise data sources, APIs, and existing systems
Technical Skills
Languages & Frameworks
- Primary: Python (FastAPI, Flask, Django), JavaScript/TypeScript (Node.js, React, Next.js)
- Secondary: Go, Rust, Java, or C# – ability to pick up new languages quickly
- AI/ML: PyTorch, TensorFlow, LangChain, LlamaIndex, Hugging Face Transformers
- Data: SQL, pandas, Apache Spark; experience with vector databases (Pinecone, Weaviate, pgvector)
- AWS: Lambda, Step Functions, Bedrock, SageMaker, S3, DynamoDB, API Gateway, ECS/EKS, EventBridge
- Infrastructure: Terraform, CloudFormation, Docker, Kubernetes, CI/CD pipelines (GitHub Actions, GitLab CI)
- AI Programming Helpers: Codex, Copilot, Claude, Cursor, Kiro
- LLM APIs: OpenAI, Anthropic Claude, AWS Bedrock, Azure OpenAI, Google Vertex AI
- Development: VS Code, JetBrains IDEs, Jupyter notebooks, Git version control
- Bachelor's degree in Computer Science, Software Engineering, or related field; or equivalent experience
- 5+ years of professional software engineering experience building production applications
- Solid experience in Python and JavaScript/TypeScript; familiarity with at least one other programming language
- Extensive practical experience working with AWS cloud platforms
- Demonstrated experience building AI/ML-powered applications with LLMs and modern AI frameworks
- Familiarity with LLM internals, prompt engineering, RAG architectures, and AI/ML principles
- Regular user of AI coding assistants with proven methods for AI-enhanced development
- Experience with containerization, serverless architectures, and infrastructure-as-code
- Strong problem-solving skills; ability to work independently and ship fast with minimal direction
- Portfolio or examples of rapidly built prototypes or applications
- Experience with fine-tuning LLMs and custom model training
- Experience in developing agentic AI systems and autonomous workflows
- AWS and/or Azure certifications (Solutions Architect, Developer, AI/ML Specialty)
- Experience with real-time applications, WebSockets, and streaming architectures
- Contributions to open-source AI/ML projects
- Experience in EdTech or learning technology industry
- Familiarity with MLOps practices and model deployment pipelines
- Full-stack development experience including modern frontend frameworks
- Velocity – Ships working code fast; optimizes for speed without sacrificing core quality
- Polyglot Approach – Comfortable across languages and platforms; picks up new tech quickly
- AI-Native Thinking – Instinctively brings to bear AI tools to amplify productivity and capabilities
- Full-Stack Versatility – Builds complete applications from infrastructure to UI
- Pragmatic Engineering – Makes smart tradeoffs; knows when "good enough" enables progress
- Self-Direction – Thrives with autonomy; doesn't wait for detailed specifications
- High-impact Core AI role building the future of AI at a leading learning company
- Freedom to work with brand-new AI technologies and development tools
- Fast-paced, innovation-focused environment that values speed and experimentation
- Direct visibility with AI leadership
- Competitive compensation and comprehensive benefits
- Professional development and continuous learning opportunities
- Flexible remote/hybrid work arrangements
Cengage is committed to working with broad talent pools to attract and hire strong and most qualified individuals. Our job applicants are considered regardless of any classification protected by applicable federal, state, provincial or local laws.
Cengage is also committed to providing reasonable accommodations for qualified individuals with disabilities including during our job application process. If you are an applicant with a disability and require reasonable accommodation in our job application process, please contact us at [email protected].
About Cengage
Cengage, a global education technology company serving millions of learners, provides affordable, quality digital products and services that equip students with the skills and competencies needed to be job ready. For more than 100 years, we have enabled the power and joy of learning with trusted, engaging content, and now, integrated digital platforms. We serve the higher education, workforce skills, secondary education, English language teaching and research markets worldwide. Through our scalable technology, including MindTap and Cengage Unlimited, we support all learners who seek to improve their lives and achieve their dreams through education.
Compensation
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.
10% Annual: Individual Target$101,900.00 - $132,450.00 USD
Skills Required
- Bachelor’s degree in Computer Science, Software Engineering, or a related field, or equivalent experience
- 5+ years of professional software engineering experience building production applications
- Professional experience with Python and JavaScript or TypeScript
- Familiarity with at least one additional programming language
- Extensive practical experience with AWS cloud platforms
- Experience building AI/ML-powered applications with LLMs and modern AI frameworks
- Familiarity with LLM internals, prompt engineering, RAG architectures, and AI/ML principles
- Regular use of AI coding assistants with proven AI-enhanced development methods
- Experience with containerization, serverless architectures, and infrastructure as code
- Strong problem-solving skills and ability to work independently with minimal direction
- Portfolio or examples of rapidly built prototypes or applications
- Experience fine-tuning LLMs and conducting custom model training
- Experience developing agentic AI systems and autonomous workflows
- AWS and/or Azure certifications
- Experience with real-time applications, WebSockets, and streaming architectures
- Contributions to open-source AI/ML projects
- Experience in EdTech or learning technology
- Familiarity with MLOps practices and model deployment pipelines
- Full-stack development experience with modern frontend frameworks
Cengage Group Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cengage Group and has not been reviewed or approved by Cengage Group.
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Leave & Time Off Breadth — Paid parental leave and company-designated wellness time off (including a year-end week off) stand out as notable time-away benefits. Flexible work positioning (virtual-first/remote-first) further increases the practical value of time-off and work-life support.
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Wellbeing & Lifestyle Benefits — Workplace mental-health support appears to be a meaningful part of the rewards package, reinforced by external recognition for mental-health practices. Wellness-oriented programs and designated wellness days contribute additional lifestyle value beyond cash pay.
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Inclusive Benefits Coverage — Benefits and policies signal strong inclusion positioning, supported by external equality recognition. Family-related supports (e.g., fertility resources and parent support) also broaden who can benefit from the package.
Cengage Group Insights
What We Do
With more than 100 years of serving learners, Cengage Group is a global edtech company that enables student choice. No matter how, where, when or why someone wants to learn, our portfolio of education businesses supports all students, from middle school through graduate school and skills education, with quality content and technology. Collectively, our three business units – Cengage Academic, Cengage Work, and Cengage Select – help millions of students each year in more than 125 countries achieve their education and career goals and lead choice-filled lives. Visit us at www.cengagegroup.com
Why Work With Us
Our employee experience centers around a shared purpose: to help millions of learners achieve their dreams and improve their lives through education. Whether you want to make a difference in the world or start a fulfilling career in edtech, we focus on providing our employees with meaningful work while empowering them with resources to succeed.
