AI Engineer – Platform & DevOps Focus (DT Experience Design)

PGC Digital (America) Inc is seeking an AI Engineer with strong platform engineering and DevOps capabilities to productionize an AI-driven UX research evaluation tool. This role focuses on backend AI engineering combined with DevOps and platform reliability, developing and deploying Python-based AI solutions as cloud-native microservices.

Responsibilities:

• Productionize and deploy Python-based AI solutions as AKS microservices following standard enterprise CI/CD patterns
• Own platform engineering and DevOps responsibilities for AI services, including build, deployment, and runtime reliability
• Maintain and enhance CI/CD pipelines (e.g., Jenkins, JFrog, Cloud Build equivalents)
• Design, deploy, and manage microservices in Azure Kubernetes Service (AKS) environments
• Implement and support authentication and access controls, including Okta-based authentication for internal users
• Set up monitoring, logging, reliability checks, and load/performance testing for AI services
• Support infrastructure configuration, environment setup, and operational readiness for production launch
• Maintain and enhance existing AI tools (including Odyssey) post-launch, supporting updates, fixes, and enhancements
• Collaborate closely with the AI innovation lead to integrate platform and infrastructure capabilities without taking ownership of core AI research or ideation
• Document architecture, deployment workflows, and operational procedures to support ongoing maintenance and handoff
• Build and maintain production-quality Python code, which represents the majority of the solution footprint
• Develop and maintain AI pipelines using frameworks such as LangChain and LangGraph
• Support agentic AI workflows and orchestration patterns
• Integrate with enterprise AI services and secrets management (e.g., Azure Key Vault, approved LLM endpoints)
• Implement AI accuracy testing, validation, and regression checks to ensure reliable outputs over time
• Support backend AI workflows and orchestration; frontend UI development is not in scope

Requirements:

• Strong Python development experience for production systems (APIs, services, pipelines)
• Hands‑on experience building and deploying AI or data‑intensive applications in production environments
• Experience developing AI pipelines and orchestration workflows (e.g., LangChain, LangGraph, or similar)
• Solid platform engineering and DevOps experience, including: CI/CD pipeline maintenance, Kubernetes‑based deployments (AKS preferred), Microservices architecture, Infrastructure reliability and monitoring
• Experience implementing authentication and secure access patterns (Okta or equivalent)
• Ability to operate effectively across AI engineering and platform engineering domains, with strength in at least one and solid working proficiency in the other
• Experience working in Azure‑based enterprise environments
• Familiarity with ServiceNow cloud infrastructure or internal tooling (helpful but not required)
• Experience supporting AI tools post‑launch, including maintenance, upgrades, and operational support
• Comfort working in fast‑moving, innovation‑driven environments where tools transition quickly from prototype to production