Among computer occupations, all other, AI is already used for a large share of the tasks. Measured exposure for computer occupations, all other: 31% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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Change management

About the job

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