Director of AI Operations – Governance

Shield AI

Director of AI Operations & Governance at Shield AI operationalizing workplace AI ecosystems. Leading AI governance and team development for enhanced operational efficiency and compliance.

Posted 7/20/2026full-timeRemote • 🇺🇸 United StatesLead💰 $280,000 - $420,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in AI and ML operations, including model training, tuning, and evaluation methodologies, while effectively managing AI governance, compliance, and cost optimization across platforms. Proven ability to lead high-performing teams and communicate complex technical concepts to executive stakeholders.

Highest-signal resume keywords

Machine Learning Model DevelopmentGenerative AI Systems ManagementAI Governance and ComplianceCost Optimization for SaaS ToolsTeam Leadership and Development

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model TrainingModel TuningModel EvaluationAI/ML Research PracticesMonitoring and Observability StacksAPI IntegrationData Science BackgroundRisk AssessmentChange ControlAudit and Logging Best Practices

Soft Skills

Executive CommunicationTeam BuildingMentoringCollaborationProblem Solving

Tools & Technologies

LLM ProvidersRPA/Workflow ToolsSaaS IntegrationsAI PlatformsOrchestration Tools

Industry Keywords

Platform OperationsDevOpsSaaS SustainmentHigh-Stakes EnvironmentData-Driven Systems

Tech Stack

Tools & technologies

RPA

About the role

Key responsibilities & impact

Evaluate, benchmark, fine-tune, and adjust configurations of ML and generative AI models (including LLMs) in production, applying working knowledge of model training, tuning, and evaluation methodologies rather than relying solely on vendor documentation.
Apply applied AI/ML research and emerging techniques to inform build-vs-buy decisions, model selection, and architecture choices across the AI portfolio.
Partner directly with data science and ML engineering teams on model performance issues, drift detection, and retraining or reconfiguration needs, contributing technical judgment rather than acting purely as a liaison.
Maintain technical fluency in prompt engineering, retrieval-augmented generation, agentic/orchestration frameworks, and the practical distinctions between generative AI and traditional ML systems, and translate those distinctions into governance and staffing decisions.
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 strategy, and building the team and processes to scale it.
Manage all AI-related 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 real-world dynamics in production.
Own and triage support tickets for workplace AI tools and platforms, driving resolution across vendors, internal engineering, and security partners.
Lead continuous evaluations of AI tools and models, including monitoring drift, benchmarking performance, and ensuring tools remain effective and aligned with business KPIs.
Maintain the updates and security outlook for AI platforms, coordinating patches, version upgrades, vulnerability remediation, and compliance with Shield AI security 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 prompt libraries, including standards for prompt quality, reuse, versioning, and training for end-users and builders.
Own management of secrets (API keys, credentials, tokens) used by AI tools and orchestrators, ensuring secure storage, rotation, and access control in partnership with Security and IT.
Define and maintain connectors and extensions (e.g., integrations into SaaS systems, data sources, and workflow tools) to ensure reliable, secure data access 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.
Lead AI governance practices for workplace AI (policies, guardrails, usage standards, approval workflows, exception processes) in partnership with Security, 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.

Requirements

What you’ll need

15+ years in platform operations, ML/AI operations, DevOps, or SaaS sustainment roles, including significant experience in leadership/people management, with a track record of running production systems in a high-stakes environment (defense, aerospace, enterprise SaaS, or similar).
Direct, hands-on experience developing, training, fine-tuning, or evaluating machine learning models or generative AI systems — this is a core requirement, not a nice-to-have. Candidates should be able to speak credibly to model architecture, training/tuning approaches, and evaluation methodology.
Working knowledge of AI/ML research practices and the ability to apply current 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.
Direct experience with AI platforms or orchestration tools (e.g., LLM providers, RPA/workflow tools like n8n, enterprise SaaS integrations) and their operational management, including at an organizational or strategic level.
Demonstrated understanding of the distinct technical and operational challenges of generative AI versus traditional ML — including differing skill requirements, risk profiles, and market/salary dynamics — and ability to apply that distinction to team design and hiring.
Strong background in governance, compliance, or security in the context of data-driven or AI systems, including familiarity with audit, logging, and access control best practices.
Demonstrated ability to manage licenses and cost optimization for SaaS or AI tools at scale, 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 fluency across APIs, connectors, and integrations; able to work closely with engineering and vendors to design and maintain extensions.
Proven track 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 clear 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 scale as the team matures.

Benefits

Comp & perks

🌐 Worldwide ❌ Jobs You've Hidden ⭐️ Saved Jobs ✅ Applied Jobs ✉️ Email Alerts 👤 Account Shield AI Website LinkedIn All Job Openings 501 - 1000 employees Founded 2015 🤖 Artificial Intelligence 🚀 Aerospace Artificial Intelligence
Aerospace
Defense Shield AI is a leading developer of AI-driven military solutions, focusing on enhancing mission autonomy and battlefield awareness. Their platform, Hivemind, enables rapid deployment of intelligent systems for various defense applications, including drone operation and surveillance. With a commitment to utilizing advanced technology, Shield AI aims to protect service members and civilians by revolutionizing defense technologies through autonomous systems. Director of AI Operations – Governance Job not on LinkedIn 🔥 7 minutes ago 🇺🇸 United States – Remote 💵 $280k - $420k / year ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence Apply Now Find Hiring Managers Customize resume + cover letter Report problem ☆ Save ☑️ Mark as applied ❌ Hide 📋 Description
Evaluate, benchmark, fine-tune, and adjust configurations of ML and generative AI models (including LLMs) in production, applying working knowledge of model training, tuning, and evaluation methodologies rather than relying solely on vendor documentation.
Apply applied AI/ML research and emerging techniques to inform build-vs-buy decisions, model selection, and architecture choices across the AI portfolio.
Partner directly with data science and ML engineering teams on model performance issues, drift detection, and retraining or reconfiguration needs, contributing technical judgment rather than acting purely as a liaison.
Maintain technical fluency in prompt engineering, retrieval-augmented generation, agentic/orchestration frameworks, and the practical distinctions between generative AI and traditional ML systems, and translate those distinctions into governance and staffing decisions.
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 strategy, and building the team and processes to scale it.
Manage all AI-related 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 real-world dynamics in production.
Own and triage support tickets for workplace AI tools and platforms, driving resolution across vendors, internal engineering, and security partners.
Lead continuous evaluations of AI tools and models, including monitoring drift, benchmarking performance, and ensuring tools remain effective and aligned with business KPIs.
Maintain the updates and security outlook for AI platforms, coordinating patches, version upgrades, vulnerability remediation, and compliance with Shield AI security 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 prompt libraries, including standards for prompt quality, reuse, versioning, and training for end-users and builders.
Own management of secrets (API keys, credentials, tokens) used by AI tools and orchestrators, ensuring secure storage, rotation, and access control in partnership with Security and IT.
Define and maintain connectors and extensions (e.g., integrations into SaaS systems, data sources, and workflow tools) to ensure reliable, secure data access 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.
Lead AI governance practices for workplace AI (policies, guardrails, usage standards, approval workflows, exception processes) in partnership with Security, 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. 🎯 Requirements
15+ years in platform operations, ML/AI operations, DevOps, or SaaS sustainment roles, including significant experience in leadership/people management, with a track record of running production systems in a high-stakes environment (defense, aerospace, enterprise SaaS, or similar).
Direct, hands-on experience developing, training, fine-tuning, or evaluating machine learning models or generative AI systems — this is a core requirement, not a nice-to-have. Candidates should be able to speak credibly to model architecture, training/tuning approaches, and evaluation methodology.
Working knowledge of AI/ML research practices and the ability to apply current 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.
Direct experience with AI platforms or orchestration tools (e.g., LLM providers, RPA/workflow tools like n8n, enterprise SaaS integrations) and their operational management, including at an organizational or strategic level.
Demonstrated understanding of the distinct technical and operational challenges of generative AI versus traditional ML — including differing skill requirements, risk profiles, and market/salary dynamics — and ability to apply that distinction to team design and hiring.
Strong background in governance, compliance, or security in the context of data-driven or AI systems, including familiarity with audit, logging, and access control best practices.
Demonstrated ability to manage licenses and cost optimization for SaaS or AI tools at scale, 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 fluency across APIs, connectors, and integrations; able to work closely with engineering and vendors to design and maintain extensions.
Proven track 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 clear 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 scale as the team matures. Apply Now 📊 Check your resume score for this job Improve your chances of getting an interview by checking your resume score before you apply. Check Resume Score Similar Jobs Director, Enterprise Strategic Programs – ERP, PMO, AI 🕒 2 days ago Veralto 10,000+ employees 🤝 B2B ⚡ Energy 🔬 Science Website LinkedIn All Job Openings Director overseeing large-scale strategic initiatives in ERP and AI for Veralto, a $5.5B technology leader. Leading governance and frameworks for enterprise transformation with cross-functional collaboration. 🇺🇸 United States – Remote 💵 $200k - $230k / year ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence Director of Embodied AI 🕒 2 days ago Stord 1001 - 5000 ☁️ SaaS 🚗 Transport 🛍️ eCommerce Website LinkedIn All Job Openings Director of Embodied AI leading the data product and customer acquisition efforts at Stord. Building a new business line in AI data operations from the ground up. 🇺🇸 United States – Remote ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence 🦅 H1B Visa Sponsor VP, Global HR Business Partner – Business AI, Technology & Product 🕒 3 days ago Circana 5001 - 10000 Website LinkedIn All Job Openings VP, Global HR Business Partner leading HR for global Business AI, Technology & Product at Circana. Driving organizational effectiveness and talent strategy in a dynamic global environment. 🇺🇸 United States – Remote 💵 $200k / year ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence VP, AI Execution 🕒 3 days ago Kaleris 501 - 1000 🚗 Transport 🏢 Enterprise ☁️ SaaS Website LinkedIn All Job Openings VP of AI Execution leading Kaleris's AI strategy and architecture, ensuring production-grade systems. Collaborate across departments to optimize AI model performance and governance. 🇺🇸 United States – Remote 💰 Venture Round on 2020-01 ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence Director, AI Evaluation 🕒 3 days ago Geisinger 10,000+ employees 💊 Pharmaceuticals 🧘 Wellness Website LinkedIn All Job Openings Director leading AI evaluation and quality assurance at Geisinger. Overseeing team of data scientists and analysts to ensure quality in AI deployments. 🇺🇸 United States – Remote ⏰ Full Time 🔴 Lead 🤖 Artificial Intelligence 🦅 H1B Visa Sponsor View More Artificial Intelligence Jobs 🌐 Worldwide Built by Lior Neu-ner. I'd love to hear your feedback — Get in touch via DM or support@remoterocketship.com Search Search Jobs by country Search jobs by city Search jobs by job title Search entry-level jobs Search junior-level jobs Search senior-level jobs Search jobs by tech stack Search jobs by contract type Search remote internships Search remote part-time jobs Remote jobs Anywhere in the World Companies Hiring Anywhere in the World Companies Hiring Sales People Anywhere in the World Companies Hiring Software Engineers Anywhere in the World Resources Advice Tips for finding remote jobs Interview questions and answers Resume examples Cover letter examples Post a job Affiliates Privacy policy Terms of service Job board SEO course AI Apply Copilot OpenClaw job finder Find jobs using your resume Jobs by Country Remote jobs anywhere in the world (Worldwide remote jobs) Remote jobs United States Remote jobs Australia Remote jobs Brazil Remote jobs Canada Remote jobs France Remote jobs Ireland Remote jobs Germany Remote jobs Netherlands Remote jobs Spain Remote jobs UK Popular Jobs Remote data analyst jobs Remote customer support jobs Remote executive assistant jobs Remote marketing jobs Remote product designer jobs Remote product manager jobs Remote project manager jobs Remote recruiter jobs Remote sales jobs Remote software engineer jobs Jobs by Type Remote full-time jobs Remote part-time jobs Remote contract jobs Remote internship jobs Remote entry-level jobs Remote jobs with no experience required Remote junior jobs (1-3 years of experience) Digital nomad jobs Remote jobs with no degree required Freelance remote jobs Temporary remote jobs Remote jobs hiring now Stay at home mom jobs