AI Platform Engineer

Requisition
176728
-Posted
10/29/2026

- Information Technology

- United States

- New Jersey

- Piscataway

- Colgate-Palmolive

- Travel - up to 10% of time

- Hybrid

No Relocation Assistance Offered
Job Number#176728 - Piscataway, New Jersey, 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.

The AI Platform Engineer is a hands-on software engineer who designs, builds, and operates the secure, scalable, governed foundation used by teams to develop and run enterprise AI applications and agents. The engineer builds and operates production-quality platform software and reusable services that support multiple business-facing products. These services may include approved model access, AI gateways, orchestration runtimes, identity and policy enforcement, evaluation, observability, deployment automation, and cost controls.

This is a hands-on software engineering role spanning platform services, APIs, distributed systems, cloud infrastructure, Dev Sec Ops , reliability, and generative AI. The primary hiring bar is demonstrated ability to design, code, test, review, deploy, and support production systems. The engineer turns enterprise architecture and governance requirements into reusable platform capabilities and standardized engineering paths that allow development teams to move quickly without recreating security, integration, monitoring, or operational controls for every solution.

• Design, code, test, deploy, and operate shared enterprise AI platform services that are secure, scalable, resilient, observable, and easy for development teams to consume.
• Write maintainable, production-quality software for platform APIs, control-plane services, data-processing components, SDKs, libraries, and developer tooling.
• Make sound software-architecture decisions covering service boundaries, interfaces, data models, concurrency, failure handling, performance, scalability, and backward compatibility.
• Implement governed access to approved foundation models and providers through gateways, APIs, SDKs, routing, quotas, authentication, authorization, and policy controls.
• Develop platform APIs, services, libraries, command-line tools, templates, and reference implementations using languages such as Python, Type Script, or Java.
• Integrate identity, SSO, service identities, RBAC/ABAC, secrets management, network controls, data-protection controls, and audit logging into platform services.
• Build automated unit, integration, security, performance, resilience, and platform-acceptance tests.
• Create developer documentation, onboarding flows, sample applications, runbooks, reference architectures, and reusable engineering standards.
• Evaluate emerging models, frameworks, runtimes, gateways, and AI infrastructure against enterprise requirements and concrete engineering use cases.
• Partner with product and application teams to improve developer experience while maintaining clear ownership boundaries between platform and product teams.
• Develop and review platform code, infrastructure-as-code, APIs, libraries, deployment pipelines, policies, automated tests, and operational tooling.
• Work with architects, security, identity, cloud, data, and application teams to turn requirements into reusable platform capabilities.
• Acts as an informal technical leader by setting platform engineering standards, reviewing designs and code, and mentoring engineers.
• May lead the delivery of a shared platform capability or coordinate technical work across cloud, security, data, and application engineering teams.

• Bachelor’s degree in Computer Science, Software engineering, Cloud engineering, Information systems, Data engineering, Artificial intelligence, or a related technical field
• Experience in either of these: relevant cloud, Kubernetes, Dev Ops, SRE, security, data, or AI certifications
• 6+ years of professional software engineering experience with demonstrated hands-on development of…