AI Engineering / AIDLC & AIOps

Role Description
AI Architect SDLC experience Agile AI savvy
Job Summary
Seeking an experienced AI Leader to drive enterprisescale AI Development Lifecycle AI Engineering and AI Operations with expertise in advanced AI technologies and cloud platforms
Job Description
Lead the organizations AI Development Lifecycle AIDLC AI Engineering practices and AI Operations AIOps across enterprise programs Define standards governance operating models and delivery frameworks for scalable secure responsible and measurable AI implementations Establish AI engineering ecosystems for rapid development deployment monitoring and continuous optimization of AI solutions Ensure compliance security reliability and business value realization in AI initiatives Drive adoption and integration of advanced AI technologies including Azure Cognitive Services Deep Learning Reinforcement Learning GenAI LLMOps and Machine Learning Lead AI platform strategy focusing on scalability performance resiliency and security Integrate ServiceNow Orchestrator to automate AI deployment and support operations Oversee AI Governance risk management and compliance aligned with ethical AI and privacy standards
Roles and Responsibilities
Define and institutionalize enterprise AIDLC frameworks methodologies and standards
Establish best practices for AI solution design development testing deployment and maintenance
Drive Responsible AI and AI Governance practices
Create reusable AI accelerators frameworks and assets
Lead AI platform architecture and engineering teams with focus on GenAI Agentic AI ML Azure Cognitive Services and Data Science delivery models
Define AI architecture standards and reference architectures ensuring system scalability performance resiliency and security
Build and govern AI Operations AIOps processes including ModelOps MLOps and LLMOps frameworks
Implement continuous monitoring model performance management and drift detection mechanisms
Define AI incident management and operational excellence processes
Drive automation across AI deployment and support ecosystems leveraging ServiceNow Orchestrator
Define AI governance policies ensuring compliance with security privacy risk and ethical AI requirements
Lead AI risk and compliance reviews
Measure success through KPIs such as AI deployment velocity model accuracy platform availability cost optimization AI adoption rate MTTR and AI ROI realization
Utilize expertise in Deep Learning Reinforcement Learning GenAI and AIOps to enhance AI capabilities and operational efficiency

Work arrangement
No