AI Engineering / AIDLC & AIOps

About the Role

Seeking an experienced AI Leader to drive enterprise-scale AI Development Lifecycle (AIDLC), AI Engineering, and AI Operations (AIOps) with expertise in advanced AI technologies and cloud platforms.

Key Responsibilities

• Lead the organization's 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.
• 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 a 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.

Requirements & Tech Stack

• Expertise in advanced AI technologies and cloud platforms.
• Experience with Azure Cognitive Services.
• Experience with Deep Learning.
• Experience with Reinforcement Learning.
• Experience with GenAI.
• Experience with LLMOps.
• Experience with Machine Learning.
• Experience with ServiceNow Orchestrator.
• Experience with ModelOps.
• Experience with MLOps.
• Experience with Agile methodologies.
• AI Architect SDLC experience.
• AI savvy.

Qualifications

• None explicitly stated in the provided text beyond the implied experience and skills.