Sr. Systems Engineer - AI

Serve as a senior-level technical leader within IT Solutions Delivery, responsible for deploying, operating, and continuously improving production AI-enabled platforms and services that support critical business applications.

 

This role ensures that AI/ML capabilities are delivered into production environments using the same operational rigor, reliability standards, and support models as enterprise IT infrastructure, enabling consistent uptime, performance, and scalability. The engineer partners closely with application teams, platform engineering, and IT operations to ensure AI services are production-ready, supportable, and aligned to enterprise operational standards.

 

Job Duties and Responsibilities:

• Deploy AI/ML solutions into enterprise production environments using repeatable, low-risk release processes
• Build and maintain automated pipelines that support solution delivery across development, testing, and production
• Ensure all AI services meet enterprise standards for deployment, configuration, and change management
• Own day-to-day operations of AI-enabled platforms, ensuring availability, reliability, and performance of business-facing services
• Establish and enforce site reliability engineering (SRE) practices, including high availability and fault tolerance, capacity planning and auto-scaling, and redundancy and failover strategies
• Continuously optimize platform performance, resource utilization, and cost efficiency
• Implement and maintain monitoring, logging, and alerting aligned to enterprise ITOM practices
• Define and track service health, performance, and data quality metrics for AI-enabled services
• Configure proactive alerting for degradations or anomalies and integrate with enterprise event management platforms
• Develop and maintain operational dashboards and visibility tools for ongoing service assurance
• Provide production support for AI-enabled services, including incident triage and resolution, performing root cause analysis (RCA), and implementing corrective and preventative actions
• Develop and maintain runbooks and support procedures to enable consistent issue resolution
• Partner with operations and service desk teams to ensure support readiness and knowledge transfer
• Integrate AI services into enterprise application and infrastructure ecosystems, ensuring compatibility with existing platforms
• Collaborate with solution delivery, infrastructure, and application teams to ensure services are fully operationalized, properly monitored, and supportable through standard IT processes
• Ensure AI components behave as first-class enterprise services within the broader application landscape
• Ensure all AI services are deployed and operated in alignment with enterprise security, compliance, and data protection standards
• Manage the full operational lifecycle of AI-enabled services, including versioning and controlled releases, performance tuning and optimization, and continuous improvement of deployment and support processes
• Identify opportunities to automate and standardize platform operations to improve efficiency and reliability
• Serve as a subject matter expert in AI platform operations
• Lead or support resolution of major incidents and complex operational challenges
• Drive adoption of standardized operational practices, including runbooks, and reliability engineering
• Provide guidance to project teams to ensure solutions are designed for production support from day one

Qualifications

Education and Experience

• Undergraduate degree in computer science, information technology, or related curriculum (or equivalent combination of experience and education)
• 8 or more years of information technology, cloud or platform engineering, DevOps, site reliability engineering (SRE), infrastructure engineering, application operations, or related experience that includes experience:
• supporting AI/ML platforms, machine learning operations (MLOps), AI-enabled applications, large-scale data platforms, or other advanced analytics environments in production
• deploying, monitoring, and supporting business-critical applications in cloud-based and hybrid enterprise environments
• designing and managing CI/CD pipelines, automated de