AI Deployment Strategist

BackOps-AI•San Francisco, CA

About The Position

BackOps is building AI-native automation for supply chain and back-office operations at the world's largest enterprises. Our products: Relay (exception detection and resolution) and the AI Process Center (workflow knowledge capture and automation), replace manual firefighting and tribal knowledge with systems that scale. We're hiring an AI Deployment Strategist to own the strategic deployment and adoption of BackOps across our largest, most strategic customers. You'll act as an embedded strategy partner inside the customer's organization, mapping how AI can reshape their operations, building internal coalitions, and driving enterprise-wide transformation. You'll design and execute deployment strategies end-to-end, architect change management approaches, and serve as the operational and strategic bridge between our AI platform and their business outcomes. This role exists because deploying AI into legacy operations isn't about implementation, it's about strategy. Our biggest customers need a partner who can diagnose where AI creates the most value, design rollout sequences that build internal buy-in, help teams rethink how they work, and orchestrate adoption at scale. You'll be that partner.

Requirements

5-8 years of experience in AI/ML implementation, digital transformation, technical strategy, or consulting. Ideally at a top-tier strategy consulting firm (BCG, McKinsey, Bain, Deloitte, Accenture) or enterprise SaaS company scaling AI products into large organizations
Strong technical foundation: you understand APIs, data architectures, integrations, and system constraints well enough to scope deployment challenges and architect solutions with engineers. You should be able to read and reason about workflows, data flows, and technical tradeoffs
Demonstrated ability to design and execute large-scale change management programs and drive adoption within complex, risk-averse organizations
Exceptional written and verbal communication. You can run a technical working session with ops teams one hour and present AI deployment strategy to a CIO the next
Proven experience building deployment playbooks, training curricula, or organizational enablement at scale
Bias toward strategic ownership: you treat customer outcomes and AI adoption success as your own responsibility and take initiative to remove obstacles
Comfort with ambiguity and ability to move quickly in a fast-moving startup environment

Nice To Haves

Background in supply chain, logistics, distribution, or back-office operations
Prior experience designing AI/ML product implementations or digital transformation programs
Prior startup or scale-up experience
Strategy consulting background (operations, digital transformation, or AI)
Experience with workflow automation, RPA, or process mining
Familiarity with enterprise change management frameworks (ADKAR, 7S model, etc.)

Responsibilities

Own the deployment strategy for our largest enterprise customers, from pre-implementation planning through org-wide AI adoption and optimization
Act as an embedded strategy advisor, diagnosing operational bottlenecks, designing AI-driven workflow redesigns, and helping customers reimagine their operating models
Build and execute multi-phase deployment roadmaps tailored to organizational readiness, stakeholder priorities, and business impact sequencing
Design and deliver training programs, enablement curricula, and change management frameworks tailored to different stakeholder groups (ops teams, managers, executives, digital transformation offices)
Partner with customer engineering, IT, and data teams on integration architecture, data governance, and technical deployment decisions
Translate customer business requirements and feedback into product strategy recommendations; work directly with engineering and product to shape the roadmap
Define and track adoption KPIs, business impact metrics, and expansion opportunities; own the strategic case for renewal and expansion alongside the founders
Design and lead POC strategy, success criteria, and graduation paths into production deployments
Identify adjacent use cases and value creation opportunities across the customer's organization