AI Engineer II - WFH

About the Company
Macmillan Publishers is one of the Big Five U.S. trade publishers and part of the Holtzbrinck Publishing Group, a global, family-owned group of media companies headquartered in Stuttgart, Germany. Macmillan publishes books across a wide range of categories and formats through imprints including Celadon Books, Farrar, Straus and Giroux, Flatiron Books, Henry Holt & Company, Macmillan Audio, Macmillan Children's Publishing Group, The St. Martin's Publishing Group, and Tor Publishing Group.
The company is modernizing its core technology platforms, developing a Publishing Operating System, and expanding the use of AI across the publishing lifecycle.
About the Role
Macmillan is seeking a Senior AI Engineer (Full-Stack / Applications) to build and operate production-grade, cloud-native applications with AI at their core. This role combines software engineering and applied AI, with a focus on turning advanced AI capabilities into reliable, scalable, user-facing products.
You will own AI-powered features from initial requirements and model evaluation through application development, deployment, monitoring, and ongoing improvement. Depending on your strengths and project needs, you may contribute to short-term proof-of-concept initiatives, rapid MVP development, or longer-term product engineering. The role also involves technical leadership, collaboration across teams, and helping shape Macmillan's technology strategy as the publishing industry adapts to AI.
Key Responsibilities
Own AI-powered features throughout the full lifecycle, from scoping and requirements engineering to evaluation, deployment, and operation.
Design, build, and maintain cloud-native, event-driven AI applications across the full stack.
Evaluate, integrate, and optimize AI models for production, balancing quality, latency, reliability, and cost.
Collaborate with technical teams and non-technical stakeholders to refine requirements and align solutions with business objectives.
Build and maintain AI inference, evaluation, and monitoring pipelines.
Develop automated evaluation frameworks for AI applications.
Analyze application performance data and experiment results to guide improvements.
Operate and improve production systems, taking responsibility for reliability, quality, and technical debt.
Keep up with AI advancements and share knowledge to support team development.
Plan, track, and break down work effectively within an agile team.
Provide technical leadership, lead design reviews, write Architecture Decision Records (ADRs), and contribute to hiring and onboarding.
Participate in on-call rotations, incident response, and post-mortems for AI-powered systems.
Help define service-level objectives (SLOs) and error budgets.
Apply clean software architecture principles, including Clean Architecture and Onion Architecture.
Implement testing practices across the stack, including unit, integration, and contract tests for deterministic code and AI components.
Apply MLOps and LLMOps practices to AI application development and operations.
Address AI safety and security risks, including prompt injection, data exfiltration, content moderation, and handling personally identifiable information (PII) and GDPR-related requirements.
Required Qualifications
Strong analytical and problem-solving skills, with a practical, results-oriented approach to ambiguity.
Clear, concise written and verbal communication skills in English, including effective asynchronous communication.
A collaborative, self-organized approach to work and a commitment to supporting team success.
Strong software engineering and AI skills, with deep expertise in at least one of the following areas:
Frontend development, including advanced React and TypeScript experience building high-quality user-facing applications.
Backend development, including designing and operating scalable, event-driven Python systems in cloud-native environments.
Applied AI, including knowledge of advanced AI models, model evaluation, integration into product features, and production best practices.
Strong theoretical understanding and practical knowledge of current AI model internals.
Experience deploying and utilizing AI models, including evaluation methods and production monitoring frameworks.
Demonstrated ownership of features from technical design through production.
Understanding of the challenges of integrating non-deterministic AI behavior into production systems.
Practical knowledge of MLOps and LLMOps best practices.
Hands-on experience with major AI service providers and their offerings.
Working knowledge of fine-tuning methods and when to apply them.
Ability to translate AI research and concepts into reliable, production-ready software.
Experience breaking complex AI objectives into requirements and actionable tasks.
Experience applying agile practices within AI/ML teams, including requirements definition, design reviews, and code reviews.
Ability to assess and adopt new technologies and frameworks quickly.
Experience building and operating cloud-native systems, ideally using Google Cloud and Firebase.
Understanding of DevOps and MLOps fundamentals, including CI/CD, observability, and Infrastructure as Code.
Working knowledge of AI safety and security practices, including OWASP Top 10 for LLMs.
Strong testing discipline across application code and AI components.
Technical leadership and mentoring experience, including guiding engineers, leading design reviews, and influencing technical direction.
Experience operating production systems and participating in on-call support.
Preferred Qualifications
Experience in the publishing or media industry.
Experience across Macmillan's technology stack, including Google Cloud, AWS, Firebase, Python, TypeScript, Django, Terraform, GitHub, Cloud Firestore, EventArc, Pub/Sub, GCIP, Cloud Storage, Cloud Functions v2, React, BigQuery, GitHub Actions, commercial AI services, open-source AI models, Langfuse, Snowflake, and PostgreSQL.
Experience with MLOps using Vertex AI and Weights & Biases.
Experience in applied research.
Experience applying Site Reliability Engineering (SRE) methodologies.
Advanced understanding of machine learning, large language models (LLMs), and developments in the AI market.
Specialized, deep expertise in a relevant technical area.
Compensation and Benefits
Base Salary: $200,000 per year.
The position is also eligible for a discretionary annual incentive program, subject to applicable plan terms.
Work Arrangement
Remote, tied to Macmillan's New York, NY office at 120 Broadway. Employment is subject to New York State tax withholding under applicable regulations.
Application Requirement
Applicants must provide a link to a LinkedIn profile, GitHub profile, Hugging Face profile, or personal portfolio to be considered for the role.
Equal Employment Opportunity
Macmillan Publishers is an equal opportunity employer committed to fostering an inclusive workplace. Qualified applicants are considered without regard to race, color, religion, age, ethnicity, national origin, sex, sexual orientation, gender identity or expression, disability, physical ability, neurodiversity, genetic information, protected veteran status, family or economic status, or any other characteristic protected by applicable law. The company prohibits discrimination and provides reasonable accommodations to qualified individuals with disabilities in accordance with applicable law.
Applicants are also provided with information about their rights under federal employment laws through the U.S. Department of Labor's Know Your Rights notice.

Work arrangement
Yes