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# Principal Software Engineer, AI Platform Enablement

- **Company:** Philip Morris International Inc.
- **Location:** United States (Remote available)
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cloud Engineering, Continuous Integration, Distributed Systems, Software Engineering, Management of Software Versions, Enterprise Software Applications, AI Platforms, Information Technology
- **Published:** October 20, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pszaq7cei5

## About the Role

* Degree in Computer Science, IT, Software Engineering or a related discipline.
 * Enterprise software engineering experience in cloud-native and distributed systems.
 * Hands-on experience engineering reusable AI platform capabilities and enterprise solutions.
 * Deep knowledge of platform engineering, developer experience and reusable AI interfaces.
 * Experience with AI services, model access, retrieval, agent tools, evaluation interfaces and SDKs.
 * Knowledge of integration contracts, dependencies, versioning, compatibility and deprecation.
 * Experience designing developer journeys, documentation and reusable engineering guidance.
 * Strong secure software architecture, CI/CD, testing and production-readiness foundations.
 * Proven technical leadership through standards, reviews, supplier assurance and remediation.
 * Strong communication, cross-team influence, mentoring and documentation skills.

Nice-to-have

 * Advanced study in AI/ML, distributed systems or cloud/platform engineering.

## Description

Join our AI Delivery & Engineering team and provide principal-level technical leadership for reusable AI platform capabilities. You'll help partners assemble secure, scalable and maintainable enterprise AI solutions through clear standards and integration patterns.

Impact You'll Own

 * Define platform enablement standards for reusable enterprise AI capabilities.
 * Improve discoverability, self-service access, integration and validation for development teams.
 * Strengthen supplier delivery through reviews of designs, code, configuration and evidence.
 * Guide decisions on reuse, integration, security, supportability, cost and lock-in.
 * Improve interface compatibility, lifecycle management and readiness across AI solutions.

What You'll Do

 * Define standards for reusable AI assets, service interfaces and integration patterns.
 * Review supplier designs, code, configurations, contracts and engineering evidence.
 * Assess whether reusable assets are secure, composable, documented and suitable for multiple use cases.
 * Guide partners on approved asset reuse, integration choices and justified exceptions.
 * Set expectations for API and SDK contracts, versioning, compatibility, migration and deprecation.
 * Review developer journeys for discovering, accessing, integrating and validating AI capabilities.
 * Turn feedback and review findings into clearer patterns, checklists and guidance.