Backblaze External Website - AI Enablement Director | LATAM
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Requirements
• Experience running an AI program across multiple functions simultaneously • Familiarity with AI governance in data-sensitive or PII-adjacent environments • Background in cloud infrastructure, storage, or technical B2B businesses • Exposure to org transitions - restructures, outsourcing programs, distributed team ramp-ups - and the workflow documentation challenges they create
Responsibilities
• Own the use case pipeline. Triage incoming requests, refine problem statements, size value, and maintain a prioritized queue across functions. Lead each use case through discovery, scoping, pilot, and launch - coordinating functional owners, IT, Engineering, Legal, and Finance as required. • Own the use case pipeline. • Do the workflow work. Conduct structured current-state assessments with department teams. Map how work actually happens today. Find where volume, repetition, or research intensity make AI a strong fit - and surface the use cases that would never appear in a top-down scan. • Do the workflow work. • Design the right solution. Evaluate whether a given workflow calls for an off-the-shelf tool, a prompt layer, a vendor product, or a custom build. Engage Engineering and IT when integration or custom development is required. Document baselines before launch. Measure the delta after. • Design the right solution. • Govern the tool stack. Own the AI vendor evaluation process end-to-end: fit assessment, security and privacy review, pilots, and build-vs-buy recommendations. Maintain the AI Tool Registry with zero ungoverned deployments. Track spend per team monthly with cost-per-outcome visibility available to the executive team. • Govern the tool stack. • Keep leadership informed. Maintain a live view of every active use case, its status, its owner, and its impact. Produce outcomes reports. Surface role and change implications early - before they become problems. • Keep leadership informed. • The Right Fit: • 7+ years in program management, business operations, or automation delivery - with direct experience moving AI or workflow automation initiatives from discovery to production • Hands-on fluency across the modern AI stack: prompt engineering, RAG pipelines, LLM orchestration, tool evaluation, and governance • Experience conducting workflow assessments with business stakeholders - not just technically, but operationally: mapping current states, identifying leverage points, designing future states • A track record of producing outcomes framed in time saved, cost reduced, or revenue impacted - not features shipped or tools deployed • Clear written communication: business cases, executive updates, solution design documents
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