Head of AI Enablement & Transformation

Voice Systems Engineering, Inc. • Bensalem Township, PA

23h • Remote

About The Position

Voice Systems Engineering (VSE) is seeking a hands-on leader to bring the company's existing AI work together and make AI a practical, governed capability across the business. This is a builder's role, not an advisory role: the successful candidate will personally prototype and ship generative AI agents, automations, and tools that enable non-engineers to use AI safely, while teaching approximately 45 employees—most of them non-technical—to apply these capabilities in their work.

The role owns VSE's AI tooling stack and vendors, skills library and agent registry, guardrails, scorecard, and targets. It has no direct reports and works through AI champions across the business, the tools it builds, and company-wide enablement sessions. The position sits in VSE's General Company Circle, its most senior leadership team, in an organization that operates using Holacracy.

The initial priority is to consolidate existing AI initiatives into one coherent, well-governed program: determine what to standardize or retire, establish appropriate guardrails, and then build on that foundation. The role will also redesign workflows with the teams doing the work, manage the use-case pipeline, evaluate build-versus-buy options, validate AI outputs, and monitor both results and employee experience.

This is a remote-based position. Applicants are currently invited from Colorado, Florida, New Jersey, Ohio, Pennsylvania, Tennessee, Texas, and Washington. VSE describes itself as remote-first and emphasizes diversity, equity, work-life balance, belonging, employee well-being, personal growth, and social responsibility.

Requirements

• Personally built and shipped agentic AI systems, automations, or LLM-powered tools that people actually use within the last 12 months.
• At least 7 years of experience in technology, operations, product, consulting, or transformation roles, including at least 2 years of applied generative AI work.
• Fluency with the current LLM ecosystem, including prompting, agents, tool use, evaluation, retrieval, workflow orchestration, and major model providers; sound judgment in assessing whether proposed ideas will work.
• Scripting or coding ability sufficient to prototype, integrate via APIs, and troubleshoot independently of an engineering team.
• Demonstrated success rolling out AI or automation across a non-technical workforce, with measurable gains in adoption, quality, or efficiency.
• Experience establishing governance, responsible-AI, or data-handling policies in a live operating environment.
• Excellent facilitation, coaching, and communication skills, with credibility among both engineers and non-technical employees.
• Comfort owning a capability end to end, with direct accountability for results and no team reporting to you.
• Care about VSE's work and the trust it has built with customers.

Nice To Haves

• Experience in a platform technology business, two-sided marketplace, or online B2C company.
• Experience consolidating scattered AI pilots or tools into one coherent, governed platform.
• Familiarity with low-code automation platforms, data pipelines, and BI tooling.
• Experience working in Holacracy or another self-management framework.

Responsibilities

• Build and ship AI capabilities, including prototypes, agents, evaluation frameworks, and a pipeline that allows non-engineers to deploy tools safely; write code most weeks.
• Lead hands-on AI enablement through weekly working sessions, role-specific playbooks, office hours, and AI champions in every function; measure adoption through actual use rather than attendance.
• Redesign core workflows around AI's capabilities in partnership with the teams performing the work.
• Own and publish the AI scorecard weekly, including missed metrics; set targets and explain transparently when and why targets change.
• Choose the AI tooling stack by evaluating models, platforms, agent frameworks, and vendors; run proofs of concept; make build-versus-buy decisions; and avoid tool sprawl.
• Establish guardrails, including a graduated autonomy model based on evidence, traceability from outputs to prompts and approvers, a permissions and data-classification model, and an acceptable-use policy developed with Legal, HR, and IT.
• Manage AI use cases from intake and prioritization through pilot, rollout, and maintenance, and openly retire at least one initiative each quarter, including initiatives of your own.
• Protect the quality of deployed AI by validating outputs against sources, retesting after model and tool updates, and defining where human oversight is required.
• Monitor whether AI is making the team more capable or more pressured; pause new AI rollouts after two consecutive weeks of declining results on this measure.

Benefits

• Unlimited vacation policy.
• Flexible work schedule.
• Comprehensive medical, dental, vision, and life insurance programs.
• Wellness wallet reimbursement for items and services including gym memberships, workout equipment, mindfulness apps, healthy food boxes, and ergonomic workspace tools.
• Tuition reimbursement and opportunities for continued learning.
• 401(k) match.
• Access to expert financial advice.

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: No Education Listed