AI Deployment Strategist

Elm AI; Northern (KY); Hybrid; USD 110,000 - 140,000; Full time

Job summary

Elm AI is hiring an AI Deployment Strategist to own customer relationships from onboarding through adoption, expansion and renewal. You’ll collaborate with customers across supply chain, sourcing, procurement and compliance to map processes and identify AI value, then partner with product and engineering to deploy solutions.

You’ll lead rollout and ongoing adoption with operators, program managers, executives and cross-functional teams, using data to measure impact and guide expansions across

Qualifications

• 3–7 years in customer success, consulting, implementation, solutions, product, operations or a related role.

Responsibilities

• Map customer workflows, SOPs, data sources and manual processes; identify high-ROI opportunities for AI.
• Translate customer needs into clear implementation requirements and work with product and engineering to deliver them.
• Lead rollout and adoption across operators, program managers, executives and cross-functional teams.
• Use customer data and usage patterns to track value, recommend improvements and identify expansion opportunities.
• Build repeatable playbooks for onboarding, workflow discovery, deployment and customer success as Elm AI grows.

Skills

Customer success

Consulting

Implementation

Solutions

Product

Operations

Program management

Data fluency

Ambiguity tolerance

Job description

Elm AI builds AI agents for sourcing, compliance and supplier operations. Our software is live with major consumer brands, helping teams manage audit reviews, corrective actions, documents and supplier follow-through across thousands of factories.

The role

We’re hiring an AI Deployment Strategist to own customer relationships from onboarding through adoption, expansion and renewal. You’ll work with customers across supply chain, sourcing, procurement and compliance to understand their processes, identify where AI can deliver measurable value, and partner with product and engineering to deploy it.

What you’ll do

• Map customer workflows, SOPs, data sources and manual processes; identify high-ROI opportunities for AI.
• Translate customer needs into clear implementation requirements and work with product and engineering to deliver them.
• Lead rollout and adoption across operators, program managers, executives and cross-functional teams.
• Use customer data and usage patterns to track value, recommend improvements and identify expansion opportunities.
• Build repeatable playbooks for onboarding, workflow discovery, deployment and customer success as Elm AI grows.

What we’re looking for

• 3–7 years in customer success, consulting, implementation, solutions, product, operations or a related customer-facing role.
• Experience with technical or enterprise software and a strong interest in practical AI deployment.
• Ability to diagnose complex workflows, define success metrics and communicate clearly with both operators and executives.
• Strong program management, data fluency and follow-through.
• Ownership and curiosity: you’re comfortable with ambiguity, getting into the details and building a playbook as you go.
• Interest in supply chains, sourcing, manufacturing, compliance, logistics, procurement or supplier operations.

Helpful, but not required: supply-chain or responsible-sourcing experience; early-stage startup experience; solutions engineering or forward-deployed work; familiarity with APIs, data models, integrations or AI agents; experience with global teams or AI-native products.

Working style

This is a hybrid role based in the United States, with meaningful overlap with U.S. Eastern Time and flexibility for customers across Europe and Asia. We offer competitive compensation, benchmarked to your role, experience and regional market.

• High ownership and direct work with founders, customers, product and engineering.
• Major global customers, several years of runway and backing from top investors.
• Room to grow into customer success, solutions, implementation or go-to-market leadership.
• Competitive compensation, a learning and development budget, generous AI and tooling budgets, and a personal spend card for experimentation and education.
• A team that values thoughtful execution, customer outcomes and sustainable work.