Director, Internal AI Operations

LaunchDarkly is looking for a strategic, execution-oriented Director of Internal AI Operations to run and continuously improve how our company adopts and scales AI, establish the operational objectives, processes, and work plans that turn AI from a collection of tools into a measurable business capability and work with leaders across several functions to put the company’s AI direction into practice.

• Reporting: Build and maintain visibility into AI spend and usage. Develop adoption, efficiency, and cost metrics and report on tool overlap, cost drivers, and open risks. Support Finance with forecasting, budget tracking, anomaly detection, and vendor and model-cost optimization. Functional and technical leaders own efficiency, waste, cost, usage, and ROI within their portfolios; AI Operations prepares regular reporting and flags performance gaps for follow-up.
• Portfolio management: Maintain the inventory of AI tools, initiatives, agents, vendors, integrations, owners, status, spend, risks, and dependencies. Establish the processes and standards that keep it accurate across teams.
• Reviews: Participate in reviewing new AI Vendor requests and own and manage the Internal AI Feature Review process from intake through decision, conditions, approval, exception, or rejection, coordinating inputs from Security, Legal, IT, and business owners.
• Policy operations: Develop and maintain the company’s Internal AI Policy supporting resources with Legal and Security, and the Executive team, along with supporting resources. Recommend policy changes and put approved changes into operation.
• Transformation and migration: Track the AI roadmap, migrations, platform dependencies, adoption milestones, resourcing, risks, and executive decisions.
• Partnership with our technology teams : Collaborate on new AI product initiatives, empowering our product teams with how they identify and deliver value around AI.
• Administration and audit: Define and audit standards for access, ownership, configuration, data controls, logging, retention, vendor settings, and offboarding.
• Communications and enablement: Own the Internal AI communications calendar, stakeholder updates, FAQs, launch materials, training coordination, and policy-change communications.
• CoE coordination: Establish a common cadence and minimum artifacts across distributed AI CoEs without centralizing their technical or domain ownership.
• 15+ years of progressively responsible experience in AI or technology operations, enterprise systems, data and analytics, FinOps, governance, transformation, or a related field, including 5+ years leading teams or complex cross-functional programs.
• Demonstrated success designing, implementing, or scaling an operating model across multiple functions, including clear ownership, policies, processes, metrics, governance, and measurable outcomes.
• Experience managing an enterprise portfolio of AI or technology tools, vendors, integrations, or platforms, including lifecycle management, access and administration, risk and controls, contracts, usage, and spend.
• Strong financial, analytical, and data-driven mindset, with experience using tools such as Snowflake, Excel, Python, or equivalent; able to define adoption, efficiency, unit economics, ROI, and business-value metrics and turn complex data into executive-ready recommendations.
• Strong financial and operational acumen, with experience building spend visibility, forecasts, budget controls, vendor or model-cost optimization, cost avoidance, waste reduction, and value-improvement plans.
• Strong written and verbal communication skills, including the ability to explain complex topics clearly, present recommendations to senior and executive leaders, and persuade diverse stakeholders.
• Experience influencing functional and technical leaders without relying on direct authority, clarifying distributed accountability, benchmarking performance, challenging tradeoffs, and driving follow-through across global, remote, and cross-functional teams.
• Curiosity and a willingness to lean into AI: able to learn emerging capabilities quickly, experiment pragmatically, identify high-value use cases, and apply sound judgment about where AI should and should not be used.
• Practical understanding of responsible AI, data governance, privacy, security, vendor risk, and change management, with the judgment to balance innovation, control, scalability, and business value.
• Strong systems thinking, program management, prioritization, and change leadership skills; comfortable bringing structure to ambiguous, company-wide problems.
• Experience hiring, coaching, or developing effective teams and building trusted partnerships across Finance, IT, Security, Legal, Procurement, and business functions.

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