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Harvard Business Publishing

AI Developer

Sorry, this job was removed at 12:19 p.m. (EST) on Thursday, Apr 02, 2026
Remote
Hiring Remotely in US
Remote
Hiring Remotely in US

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Harvard Business Publishing (HBP) – the leading destination for innovative management thinking. We reach lifelong learners to improve the practice of management in a changing world. This mission inspires each of us to unlock the leader in everyone – including you!

The opportunity:

The AI Developer (AID) at Harvard Business Publishing (HBP) will play a pivotal role in driving innovation and enhancing the company's product offerings through the application of AI and ML technologies to enhance the value delivery and interactivity of our product experiences across diverse modes of engagement. This position involves supporting product teams in rapid prototype development to test and learn about new product experiences, supporting and equipping product leads with knowledge and tools to help them pursue new AI-enabled product concepts, and facilitating collaboration cross-functionally to leverage core ML and AI infrastructure throughout HBP. The ideal candidate will have a strong background in AI development, experience with ML infrastructure, and a passion for innovation.

What You’ll Do: 

  • Support product teams in building new AI-enabled features: Contribute to technical vision and participate directly as a technical resource in product development, focusing on innovation with data and AI to create cutting-edge solutions. Work closely with HBP product teams to develop and iterate on prototypes quickly, ensuring that AI and ML capabilities are effectively integrated into new product ideas and that we can test and learn more quickly over time by reusing shared AI capabilities

  • Facilitate technical interoperability: Act as a bridge between HBP product management, data engineering, production software engineering, and partner technical teams at HBP and HBS to extend and leverage core ML and AI infrastructure across development stages from prototyping to production

  • Develop and maintain ML and AI infrastructure: Work in consultation with partner technical teams at HBP and HBS to develop and maintain the infrastructure needed for product-facing ML and AI applications, such as an LLM chat interface, a vector store for RAG, predictive ML workflows with automated triggers, and ML Ops tools, within AWS and snowflake environments

  • Contribute to data engineering: Ensure quality and integrity of user, content, and market data by collaborating with the Data Engineering team to build and maintain data pipelines and product-facing APIs for HBP's central data warehouse relevant to products the AID is supporting

  • Support data science and analytics: Contribute to design and execution of data science and analytics projects relevant to products the AID is supporting, such as inferring causal factors driving user intent, predicting user attributes, exposing insight from user activity to inform editorial and marketing decisions, and projecting potential revenue

What you'll bring: 

  • Experience: 5+ years in data science, ML/AI development, or a closely related field, with a proven track record of delivering production-grade AI/ML solutions

  • Collaboration: Excellent communication and stakeholder management skills, with the ability to work effectively across multiple teams and departments.

  • Innovation: A strong passion for innovation and the ability to think creatively about how AI and ML can be applied to solve business problems and enhance product offerings

  • ML Infrastructure: Hands-on experience with developing, deploying, and maintaining ML infrastructure, including model training, evaluation, and production-ready APIs. Familiarity with MLOps tools and concepts including MLFlow, AWS Sagemaker, model registries, and CI/CD. Experience delivering AI/ML APIs using FastAPI, flask, or similar.

  • Programming Skills: Excellence in Python programming and experience with relevant data science and AI/ML packages such as pandas, scikitlearn, pytorch, and Langchain. Extensive experience in collaborative development with git

  • Cloud Services: Practical experience with cloud services such as AWS (preferred), Azure, or Google Cloud for deploying and managing AI/ML workflows and containerization tools like docker

Preferred/Nice to Have:

  • Gen AI experience: 3+ years of experience developing products with, and guardrails for, LLMs strongly preferred

  • No-Code AI Tools: Experience support end users of no-code AI-assistive tools and platforms and ability to support transitions of no-code prototypes to dev and production environments

  • Data Engineering: Familiarity with data engineering concepts and tools, including data pipelines, ETL processes, data warehousing, the medallion architecture, and dbt

  • Data science: Extensive experience answering questions with and deriving strategic insights from data, including proficiency in probability and statistics, data querying and transformation with SQL, and developing interactive data dashboards and applications with tools like Streamlit

What we offer:

As a mission-driven global company, Harvard Business Publishing is committed to fostering a culture of inclusion, trust, and engagement where everyone is welcome, valued, respected, and feels they belong. In addition to a competitive compensation and benefits package, we offer meaningful programs focused on career development and employee wellness, such as education reimbursement and early-release Summer Fridays!

HBP is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.

$150,000 - $170,000

Above is the annualized pay range for this position. In addition, this position includes the opportunity to earn our annual Performance Based Variable Pay Program. Actual salary will be set based upon a range of factors, including external benchmark market data, individual knowledge, skills, experience, location and internal equity. 

Harvard Business Publishing New York, New York, USA Office

3 Columbus Circle, Suite 2210, New York, New York, United States, 10019

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