Required Education
-Bachelor's degree in Computer Science, Data Science, Engineering, Information Systems, or a related field, or equivalent practical experience.
Required Skills
-Advanced experience supporting enterprise AI/ML, Generative AI, cloud, platform engineering, or production application environments.
-Hands-on experience with Azure cloud services, application hosting, monitoring, logging, and production support practices.
-Experience with incident, problem, change, release, and service-request management in an enterprise environment.
-Experience supporting CI/CD pipelines, automated infrastructure provisioning, and deployment processes.
-Demonstrated ability to lead complex troubleshooting, root cause analysis, technical coordination, and service restoration.
-Strong written communication, operational documentation, stakeholder management, prioritization, and escalation-management skills.
-Generative AI and AI/ML platform operations
-Microsoft Azure cloud services and hosted application environments
-Azure DevOps, CI/CD pipelines, and automated infrastructure provisioning
-ServiceNow or equivalent enterprise service-management tooling
-Monitoring, logging, diagnostics, performance testing, and root cause analysis
-Production support, release management, operational resilience, and technical documentation
Nice to Have:
-Experience with Generative AI platforms, LLMOps, MLOps, model-serving environments, or shared enterprise AI services.
-Experience onboarding enterprise applications or TLAs to a common platform.
-Knowledge of Infrastructure as Code, cloud-native architecture, observability, resiliency, and performance engineering.
-Experience guiding distributed onsite and offshore support resources.
The Lead AI Platform Engineer / GAI Platform Operations Lead is the senior technical resource accountable for the operational reliability, productionization, optimization, and continuous improvement of the enterprise Generative AI platform.
Tasks & Responsibilities:
-Lead deployment, management, and optimization of GAI platform resources across non-production and production environments.
-Own Level 3 investigation and resolution of complex platform, application, infrastructure, access, deployment, integration, and performance issues within agreed service expectations.
-Develop and mature repeatable platform onboarding processes for applications and TLAs, including readiness, access, infrastructure, deployment, and upstream/downstream integration dependencies.
-Coordinate with delivery teams, cloud infrastructure, security, application teams, and service providers to support smooth execution and service restoration.
-Establish continuous monitoring, logging, performance testing, capacity analysis, and proactive issue identification for deployed infrastructure and applications.
-Analyze platform and application logs, identify root causes, and direct corrective and preventive actions through closure.
-Lead support for DevOps pipelines, automated infrastructure provisioning, release activities, configuration, patching, maintenance, and productionization.
-Act on incidents, requests, defects, and problem records in accordance with defined escalation processes and SLAs.
-Create and maintain technical standards, runbooks, playbooks, troubleshooting guides, onboarding procedures, and operational knowledge.
-Identify and implement opportunities to strengthen resilience, reduce production incidents, decrease manual effort, and increase automation.
-Provide clear stakeholder communications regarding service status, incident progress, risks, dependencies, SLA performance, and required actions.
-Demonstrate a self-starter mindset by proactively identifying, owning, and driving work through completion with limited oversight.
-Think in systems by understanding complex processes, recognizing cross-functional dependencies, and solving interconnected problems across platform, application, infrastructure, and operational domains.
-Provide technical direction and escalation support to L1/L2 GAI Operations Support Engineers.
-Stable and supportable GAI platform services across lower and production environments.
-Repeatable application and TLA onboarding processes and supporting documentation.
-Completed incident resolutions, root cause analyses, and corrective/preventive action tracking.
-Maintained monitoring, performance-testing, runbook, playbook, troubleshooting, and operational documentation.
-Automation and resilience improvements that reduce manual effort and recurring production incidents.
-Performance and Success Measures:
-Platform availability, reliability, and production stability.
-Resolution of escalated incidents within applicable service expectations and SLAs.
-Quality and timeliness of root cause analysis, corrective actions, and stakeholder communications.
-Effectiveness of onboarding, automation, monitoring, and operational-maturity improvements.
-Reduction of recurring incidents, manual support effort, and avoidable escalations.
-Collaborate with GAI platform engineering, application delivery, cloud infrastructure, cybersecurity, service management, and business stakeholder teams.
-Coordinate with third-party providers and distributed onsite/offshore support resources as required.
-Follow applicable Northern Trust SDLC, security, change-management, incident-management, access-control, and documentation requirements.
-Use designated systems for issue logging, tracking, knowledge management, and closure.
-Maintain accurate, timely, and audit-ready operational records and stakeholder communications
