AI Engineer

Position: AI Engineer (703)
Job Title AI Engineer Platform & Dev Ops Focus (DT Experience Design)
Location US Remote
Duration 3 Months, with potential extension based on outcomes
Focus: Backend AI engineering, platform engineering, and Dev Ops (not frontend UI)

Job Description:
Service Now Digital Technology Experience Design is seeking an AI Engineer with strong platform engineering and Dev Ops capabilities to product ionize an AI driven UX research evaluation tool. This role is responsible for developing, deploying, and operating Python based AI solutions as cloud native microservices, while partnering closely with the AI innovation lead. The focus is backend AI engineering combined with Dev Ops and platform reliability, not frontend UI development.

Key Responsibilities
Productionize and deploy Python based AI solutions as AKS microservices following standard enterprise CI/CD patterns.
Own platform engineering and Dev Ops 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.

AI Engineering Responsibilities
Build and maintain production quality Python code, which represents the majority of the solution footprint.
Develop and maintain AI pipelines using frameworks such as Lang Chain and Lang Graph.
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.

Required Qualifications
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., Lang Chain, Lang Graph, or similar).
Solid platform engineering and Dev Ops 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.

Preferred Qualifications
Experience working in Azure based enterprise environments.
Familiarity with Service Now 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.