Director, AI Engineering

Relocation Assistance Offered Within Country
Job Number #171674 - New York, New York, United States

Who We Are

Colgate-Palmolive Company is a global consumer products company operating in over 200 countries specializing in Oral Care, Personal Care, Home Care, Skin Care, and Pet Nutrition. Our products are trusted in more households than any other brand in the world, making us a household name!

Join Colgate-Palmolive, a caring, innovative growth company reimagining a healthier future for people, their pets, and our planet. Guided by our core values—Caring, Inclusive, and Courageous—we foster a culture that inspires our people to achieve common goals. Together, let's build a brighter, healthier future for all.
 

Purpose:

The Director of AI Engineering is the lead of Colgate-Palmolive’s Enterprise AI Engineering team. This leader is responsible for managing a high-impact team of AI engineers who will architect the next generation of enterprise AI infrastructure, specifically focusing on AI communication protocols, agentic platforms, context management systems, verification frameworks, and emerging technologies. As the head of the AI engineering for the enterprise, you will also lead a team of elite AI Engineers to transform high-priority enterprise "moonshots" into production-grade realities that drive measurable business value across Marketing, Supply Chain, and Innovation verticals.

 

Core Responsibilities:

• Enterprise AI Architecture: Own the technical design and roadmap for the enterprise AI ecosystem, including the evolution of agentic workflows, enterprise context and knowledge graphs, secure routing services (eg. MCP), and integrated HITL workflows.

• Core AI Lab Leadership: Direct the company’s internal AI Lab to rapidly prototype emerging technologies, setting the standard for agile forward deployed engineering to deliver rapid value on critical high-visibility projects.

• Priority Project Delivery: Act as the lead technical partner for high-stakes enterprise Vertical Priorities, across functionals and global businesses. 

• Standards & Governance: Establish enterprise-wide engineering standards for Evaluation Frameworks, ensuring all AI agents and models are reliable, ethical, and compliant with Global AI Governance.

• Infrastructure Ownership: Define the tech stack for context management, RAG architectures, agent communication, vector database implementations, etc to create leading-edge AI infrastructure and architectures.

 

Required Qualifications: 

• Bachelor’s Degree in Computer Science, Artificial Intelligence, Software Engineering, or a related technical STEM field.
  
  
• Leadership: 5+ years of experience in AI or software engineering, with at least 3 years in a leadership role managing technical teams.
• Agentic Frameworks: Proven ability to build E2E AI-powered solutions using modern AI frameworks like n8n, Vercel, Langgraph, etc.
• AI at Scale: Experience deploying production-grade AI applications. 
• Modern Tooling: Expert hands-on proficiency - able to lead from the front and dive into technical problems when needed.

Preferred Qualifications: 

Master's in a quantitative field (e.g., Computer Science, Statistics, or Physics).

Preferred experience working in matrixed global organizational structures.

Technical Skills:

• Architectural Mastery: Deep understanding of Software and architecture best practices. And latest frameworks in AI stack, including Model Context Protocol (MCP), A2A, RAG architectures, and semantic search, context graphs, etc.

• Orchestration & Coding: Mastery of LLM orchestration and high-level competency in a major programming language.

• MLOps & DevOps: Expert knowledge of containerization (Docker/Kubernetes) and CI/CD frameworks specifically for the ML lifecycle.

• Data Integrity: Familiarity with pipeline orchestration tools like Airflow and dbt to ensure high-quality, AI-ready data foundations.

 

Core Competencies:

• Problem-solving: Ability to decompose complex enterprise challenges into modular, agentic AI solutions.

• Executive Communication: Exceptional ability to explain highly technical architectural concepts to non-technical stakeholders and C-suite executives.

• Project Management: Excellence in managing a portfolio of complex AI initiative