AI Engineer

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.

You will build prototypes that prove business value and technical feasibility.

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.

About North America

We believe in the power and joy of learning 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.

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.

Responsibilities

• Your role involves turning concepts into functional applications, not simply mock-ups or wireframes.
• 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 AI-Assisted & AI-Forward Development 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
• Engineering & Infrastructure 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 AI/ML Integration & Engineering 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

Requirements

• The ideal applicant is proficient in modern programming languages and has strong experience working with AWS services.
• 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)
• 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 Creation Tools 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
• Qualifications 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

Preferred

• Qualifications 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
• Key Competencies 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

Pay

• 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

Benefits

• 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.
• 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.

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] .