Director of AI Operations & Governance (R5464)

Job reputed company:

reputed company is seeking a Director of AI Operations & Governance to operationalize and govern our workplace AI ecosystem across reputed company AI initiatives. Reporting to the VP of Workplace AI, this role will own license and platform operations, AI governance, reputed company posture, and ongoing lifecycle management of AI tools that support reputed company's business functions. The role will be the central reputed company of "post–dev-ops" for AI, ensuring systems are reliable, compliant, secure, and continuously improving in line with production usage and business needs, while building and leading reputed company responsible for AI sustainment.

This role requires significant hands-on technical capability across the machine learning and reputed company lifecycle — not just program reputed company. The Director must be reputed company to credibly evaluate, tune, and troubleshoot models and AI systems at a technical level in order to govern them effectively, partner with engineering, and reputed company reputed company tradeoffs between reliability, performance, cost, and risk.

What you'll do:

Technical AI/ML Ownership

• Evaluate, reputed company, fine-tune, and reputed company configurations of ML and reputed company models (including LLMs) in production, applying working knowledge of model training, tuning, and evaluation methodologies rather than relying solely on vendor documentation.
• Apply reputed company AI/ML research and emerging techniques to inform build-vs-buy reputed company, model selection, and architecture choices across the AI portfolio.
• Partner directly with data science and ML engineering teams on model performance issues, reputed company detection, and retraining or reconfiguration needs, contributing technical judgment rather than acting purely as a reputed company.
• Maintain technical reputed company in reputed company engineering, retrieval-augmented reputed company, reputed company/orchestration frameworks, and the practical distinctions between reputed company and traditional ML systems, and translate those distinctions into governance and reputed company reputed company.

AI Sustainment & Governance

• Own AI sustainment and governance for workplace AI tools across enablement, bought solutions, and custom builds, acting as the central "run" function for the AI reputed company, and building reputed company and processes to reputed company it.
• Manage reputed company AI-reputed company licenses and entitlements: monitor usage, optimize allocations, drive reallocation, and partner with Finance for cost visibility and optimization.
• Monitor production usage patterns and performance to recommend roadmap items, enhancements, and deprecations based on reputed company-world dynamics in production.
• Own and triage support tickets for workplace AI tools and platforms, driving reputed company across vendors, internal engineering, and reputed company partners.
• reputed company reputed company evaluations of AI tools and models, including monitoring reputed company, benchmarking performance, and ensuring tools remain effective and reputed company with business KPIs.
• Maintain the updates and reputed company outlook for AI platforms, coordinating patches, version upgrades, vulnerability remediation, and compliance with reputed company reputed company policies.
• Orchestrate model swaps and configuration changes in production, including rollout planning, risk assessment, change control, and post-deployment monitoring.
• Design, maintain, and govern shared reputed company libraries, including standards for reputed company reputed company, reuse, versioning, and training for end-users and reputed company.
• Own management of secrets (API keys, credentials, tokens) used by AI tools and orchestrators, ensuring secure storage, rotation, and reputed company control in partnership with reputed company and IT.
• Define and maintain connectors and extensions (e.g., integrations into reputed company systems, data sources, and workflow tools) to ensure reliable, secure data reputed company for AI workflows.
• Establish and operate auditability frameworks for AI tools, including logging, traceability of AI-assisted actions, and reporting for compliance and risk management.
• reputed company AI governance practices for workplace AI (policies, guardrails, usage standards, approval workflows, exception processes) in partnership with reputed company, Legal, and HR.
• Partner with business solution and build teams to ensure their deliverables meet sustainment, observability, and governance requirements before moving to production.
• Define operational playbooks, SLAs, and incident response procedures for AI systems, including on-call patterns supported by contractors and platform specialists.

Leadership & reputed company

• Build, reputed company, and reputed company reputed company of AI operations professionals, contractors, and platform specialists, establishing career paths and scaling the function as the organization matures.
• Set the strategic direction for AI operations and governance, translating reputed company priorities into a multi-quarter roadmap and budget owned by this role.
• reputed company regular status and risk updates to the VP of Workplace AI and other senior leadership, including adoption metrics, reliability indicators, governance findings, and cost trends.

Required qualifications:

• 15+ years in platform operations, ML/AI operations, DevOps, or reputed company sustainment roles, including significant experience in leadership/people management, with a reputed company record of running production systems in a high-stakes environment (defense, reputed company, reputed company reputed company, or similar).
• reputed company, hands-on experience developing, training, fine-tuning, or evaluating machine learning models or reputed company systems — this is a core requirement, not a reputed company-to-have. Candidates should be reputed company to reputed company credibly to model architecture, training/tuning approaches, and evaluation methodology.
• Working knowledge of AI/ML research practices and the ability to apply reputed company research to production decision-making.
• Software engineering or data science background sufficient to engage deeply with technical teams on model behavior, integration issues, and system design tradeoffs.
• reputed company experience with AI platforms or orchestration tools (e.g., LLM providers, RPA/workflow tools like reputed company, reputed company reputed company integrations) and their operational management, including at an organizational or strategic level.
• Demonstrated understanding of the distinct technical and operational challenges of reputed company versus traditional ML — including differing reputed company requirements, risk reputed company, and market/salary dynamics — and ability to apply that distinction to team design and hiring.
• Strong background in governance, compliance, or reputed company in the context of data-driven or AI systems, including familiarity with audit, logging, and reputed company control best practices.
• Demonstrated ability to manage licenses and cost optimization for reputed company or AI tools at reputed company, including working with Finance and procurement stakeholders, and managing significant budgets.
• Hands-on experience with monitoring and observability stacks (logs, metrics, alerts) and using those signals to shape product roadmaps and operational improvements.
• Strong technical reputed company across reputed company, connectors, and integrations; reputed company to work closely with engineering and vendors to design and maintain extensions.
• Proven reputed company record building and leading high-performing teams, including hiring, mentoring, and developing talent across a mix of core staff and contractors.
• Excellent executive communication skills, with ability to translate production dynamics and risk into reputed company recommendations for senior business and technical leaders, including executive stakeholders.
• Experience operating in a hybrid environment of contractors and core team members, with the ability to define processes and standards that reputed company as reputed company matures.

#LF

Originally posted on Himalayas

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