Director, AI Operations – Optimization

Responsibilities

• Lead enterprise AI operational activities, including runtime monitoring, operational support, incident management, production reliability, and operational continuity for AI-powered applications and intelligent automation solutions.
• Establish, implement, and continuously improve AI operational practices, including AIOps and LLMOps processes, runtime observability, operational telemetry, drift detection, release coordination, support workflows, and operational readiness activities.
• Drive runtime stability and service reliability initiatives through production monitoring, escalation management, root cause analysis, operational playbooks, and service continuity practices.
• Support enforcement of runtime governance standards, operational safeguards, human oversight controls, and secure operationalization practices for enterprise AI solutions.
• Ensure operational excellence across AI environments through proactive monitoring, issue prevention, and continuous service improvement efforts.
• Lead initiatives focused on runtime efficiency, operational scalability, inference utilization, supportability, performance optimization, and sustainable AI operations.
• Promote standardized operational processes, scalable support models, automation opportunities, and continuous improvement initiatives across AI operations functions.
• Drive operational maturity by identifying opportunities to enhance performance, reduce operational risk, and improve support effectiveness.
• Partner closely with AI Engineering & Delivery, AI Governance, AI Quality Engineering, Automation, Architecture, Platform Engineering, Security, Infrastructure, and business stakeholders to ensure operational readiness and runtime reliability.
• Coordinate operational execution activities across AI operations teams, including operational planning, vendor and contractor management, issue prioritization, escalation management, knowledge transfer, and delivery continuity.
• Support operational assessments, production readiness reviews, implementation planning, runtime support strategies, and modernization initiatives for prioritized AI capabilities.
• Collaborate with technical and business leaders to align operational practices with enterprise AI objectives and service expectations.
• Lead, mentor, and develop operations managers, engineers, analysts, and contractor resources while fostering a high-performing, collaborative, and continuously learning culture.
• Provide clear communication regarding operational performance, runtime risks, service reliability concerns, optimization opportunities, engineering tradeoffs, and strategic recommendations.
• Establish accountability for operational outcomes while promoting operational discipline, innovation, and continuous improvement.
• Research and evaluate emerging AI operational technologies, observability platforms, automation capabilities, optimization techniques, and runtime management practices to drive innovation and operational effectiveness.

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Technology Management, or a related field preferred.
• 8+ years of experience in AI operations, software engineering, platform operations, engineering delivery, Dev Ops, Site Reliability Engineering (SRE), infrastructure operations, or related enterprise technology functions required.
• 3+ years of experience leading operational teams, engineering support organizations, platform operations, or large-scale technology initiatives required.
• Hands‑on experience supporting, operationalizing, monitoring, or optimizing production AI solutions utilizing large language models (LLMs), APIs, agentic workflows, orchestration frameworks, and modern AI engineering practices required.
• Strong experience implementing and scaling operational support models, observability practices, incident management processes, Dev Ops methodologies, runtime operations, or enterprise operational frameworks required.
• Experience with observability platforms, monitoring tools, incident management processes, runtime operations, CI/CD pipelines, and production support practices required.
• Experience leading distributed teams, managing…