Director of AI

WM Synergy is a 40-year ERP and business transformation partner for SMB manufacturers and distributors. We are executing a strategic pivot from an ERP services firm to an Outcomes Company for SMB Manufacturers and Distributors, powered by both ERP + AI.

We have started building the foundation with an AI Council, Practitioner Academy, 100+ internal skills, 25+ active Claude CoWork/Code/Design users, governance in flight. But the path forward is still being shaped, and we need a leader who can help shape it. The right person brings their own perspective on where AI is going in our space, challenges our assumptions, and partners with the CEO & CSO and entire ELT to set the vision, and then runs the practice that delivers against it.

This is a builder role for someone who wants to define what AI looks like at a 25-year services firm transitioning into something new. You will lead a small, focused team, coach our consultants and engineers, and turn our deep manufacturing and distribution expertise into productized AI offerings that customers pay for. You will grow into a larger role as the practice scales.

Vision and Strategic Partnership

• Partner with the CEO, CSO and ELT to shape and continuously refine the WM Synergy AI strategy. Bring your own point of view on where AI is going in mid-market ERP, where the moat is, and where the bets should be placed.
• Create and continuously communicate a shared vision of where the AI practice is going. Translate market signals, customer needs, and competitive moves into a roadmap the team can execute against.
• Surface market and customer signals back to the ELT. You are our eyes on the AI landscape. Push back when you see us missing something.

Team Leadership

• Lead a small, focused AI team and hire and develop 1 to 2 Business Analysts, agent engineers, and/or AI experts in year one. Add fractional or part-time specialists as needed (FinOps, evaluations, data engineering).
• Coach and support our consultants, functional and technical, and software engineers as they learn to build agents, ERP customizations, reports, and productized IP based on their industry expertise. Goal is to make 130+ delivery professionals more capable and watch for Agents that can be used across multiple customers.
• Run the AI Practitioner Academy. Grow the Skill Library. Make AI fluency a baseline expectation, not a specialization.

Customer Feedback and Productized Agents

• Run the customer feedback loop. Sit in on flagship reference customer engagements, listen for what customers actually need, and feed it back into the roadmap. Customer-led, not vendor-led.
• Deliver the productized agent roadmap. Build 3 to 5 industry-specific agents in year one tied to manufacturing and distribution workflows.
• Partner with Sales and Delivery to support customer-facing AI engagements, from scoping through deployment and optimization.

AI Spend Management (FinOps)

• Own all internal AI spend: Anthropic, open-source infrastructure, and so on. Build cost dashboards, model-routing policies, and consumption governance.
• Establish token discipline as a team practice: bounded-loop design, model tiering, caching, prompt optimization, evaluations.
• Build AI FinOps as an external service line, assessment, governance, model selection, value tracking, turning the discipline we build internally into recurring customer revenue.

Idea-to-Production Factory

• Run the Idea-to-Production Factory in partnership with the AI Council. Intake, prototype, evaluate, productize, retire. Kill quickly. Scale what works.
• Maintain the AI Project Submission Form, value-per-token forecasts, and reliability standards (bounded loops, evaluation criteria, human-checkpoint design).

Tool, Architecture, and Reliability Standards

• Own the decision framework for when we use Claude/Cowork, when we use Velocity Suite, when we use Acumatica's native AI, and when we use open-weight models. Maintain the architecture standards across the team.
• Make reliability an economic discipline. Every agent we ship has bounded loops, evaluation criteria, and human-in-the-loop checkpoints.

WHAT SUCCESS LOOKS LIKE (12 TO 18 MONTHS)

• A shared, articulated vision for the AI practice that the team, the ELT, and our customers can repeat back to you.
• 100% of consultants badged in the AI Foundations Track. Skill Library at 200+ skills.
• 3 to 5 productized agents in market with named flagship reference customers.
• AI FinOps offering stood up internally and proven out, with the first customers landed.
• Internal AI spend tracked, attributable, and under approved budget.
• The team you have built is capable, focused, and ready to scale. You are ready to grow into a VP or Chief AI role as the practice expands.

REQUIRED QUALIFICATIONS

• 5+ years of relevant experience.
• Hands-on AI builder. Direct experience with Claude/Anthropic, agent frameworks, RAG, and evaluation systems. You can architect and ship, not just delegate.
• Track record of leading small, high-performing teams across technical and functional disciplines.
• Strong commercial instincts. Comfortable with margin profiles, pricing conversations, and customer-facing engagements.
• Experience in SMB or mid-market services, ideally in manufacturing, distribution, ERP, or adjacent industries.

Technical Depth We Expect

• You ship production agents, not demos. Hands-on with agent frameworks, RAG and retrieval, and evaluation tooling, and you build in the reliability basics every agent needs: bounded loops, eval criteria, monitoring, and human checkpoints.
• You can read and write code and make the architecture calls, not just delegate them. Comfortable working in a modern cloud and wiring agents into ERP, CRM, and operational systems through clean APIs and trustworthy data.
• Strong handle on AI cost. Token economics, model tiering and routing, caching, and consumption tied to a real budget.

PREFERRED QUALIFICATIONS

• Exposure to Acumatica, Sage Intacct, Infor, or comparable mid-market ERP ecosystems.
• Background that blends startup builder energy with services-firm discipline.
• Has stood up an AI program or center of excellence, including the operating model, governance, and the path from proof of concept to production.
• Experience driving AI adoption across delivery teams with tools like Claude Code, GitHub Copilot, or Cursor.

PERSONAL ATTRIBUTES

• Strategic thinker and hands-on builder. Comfortable shaping a vision and shipping the work that proves it out.
• Servant leader. Coaches the team, does not take credit for the team.
• Customer-obsessed: knows when to listen and when to push back.
• Strong opinions, loosely held. Brings a point of view, but listens hard and updates fast.
• Direct, accountable, low-ego, high-transparency.
• Ambitious, wants to grow this role into a larger one as the practice scales.

• Direct reporting line to the ELT. Hands-on visibility, real authority, and real accountability.
• A working AI foundation already in place: AI Council, Practitioner Academy, 100+ skills, approved budget, 25+ active users.
• A clear promotion path. As the practice scales and delivers measurable outcomes, this role grows into VP, AI Strategy & Practice or Chief AI Officer.
• Competitive base, performance incentives, and equity participation aligned to the company's growth plan.
• Remote work, with regular customer and office travel.

Salary for this role is between 200k and 240k

#INDMM