Head of Product, AI Workforce
Wand Synthesis AI Inc • Remote, Europe Timezone
Posted: May 22, 2026
Job Description
Build the Future Workforce
Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. And it’s already operating at scale inside some of the world’s largest organizations.
Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.
Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy. We’re building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale.
Join Wand in leading the Agentic Shift
Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers.
You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern.
Position Summary
You'll lead the product team defining what an "agent" actually is. This means owning the core AI workforce product: execution, process automation, communication, and skills/training. This role combines hands-on product development with thought leadership on agentic AI while shipping to enterprises with 50k+ employees.
You'll own the AI Workforce product stream including agent execution, workflows, communication, and skills & university (training/maturation). You'll define product strategy and roadmap for the core agentic system, establish the definition of "what is an agent" for the company and industry, and lead Skills & University where we train models, optimize prompts, and mature agents with organizational context. You should be able to explain to the CEO and CTPO what an agent really means.
Responsibilities
Lead product for 4 teams: execution, process automation, communication, skills & university
Spend significant time in skills & university, the core innovation area for agent training and maturation
Define agent architecture: Is a process an agent? Is an agent a human replacement? These are nuanced questions you'll answer.
Ship features that work for enterprises, not just demos for engineers
Work closely with your engineering counterpart to balance innovation and execution
Participate in EPD leadership and shape overall product direction
Build credibility as someone who can write or speak authoritatively on agentic AI
Ship agent training and maturation system (skills & university) to production in first 12 months
Define and document "what is an agent" framework adopted across the company
Lead 3+ enterprise customer implementations and iterate product based on feedback
Publish or present thought leadership on agentic AI externally
Reduce ambiguity in agent architecture so engineers know what they're building
Key Qualifications
Director-level Product Manager or Group Product Manager
Hands-on experience building agentic AI systems (non-negotiable)
ML/AI product background required with substantial depth in the field
Experience with LLM training, prompt optimization, or agent frameworks (n8n, CrewAI, Sierra, etc.)
Enterprise product sense: you understand org processes, compliance, separation of concerns
Ability to go deep technically and explain agent architecture to engineers
Coming from product organizations, not engineering or research
Preferred Experience
Built vertical AI products serving enterprises
Worked on agentic systems that went to production, not just prototypes
Experience defining "what is an agent" at both the conceptual and implementation levels
Background in skills training systems or model maturation platforms
Personal Characteristics
Thought leader mindset with ability to influence industry direction
Hands-on approach, not just strategic oversight
Deep technical curiosity about agent architecture and capabilities
Strong communication skills for explaining complex concepts
Comfortable with ambiguity and defining new categories
Bias toward shipping and learning from production deployments
Additional Content
Build the Future Workforce
Wand turns AI into labor. It enables humans and AI agents to operate together as a unified, hybrid workforce, with comprehensive management and oversight. And it’s already operating at scale inside some of the world’s largest organizations.
Wand built the world’s first Agentic Labor Infrastructure enabling governments and global enterprises to create, manage, and scale digital workforces.
Our mission is to integrate agent ecosystems into the core of work and business, unlocking a generational leap in the global economy. We’re building the infrastructure that lets humans and AI agents operate together safely, transparently, and at scale.
Join Wand in leading the Agentic Shift
Wand is building a high-performing global team who take full ownership of what they build. We lead by example, move fast, make data-aware decisions, and continuously push for more- always with a focus on delivering real value to customers.
You would be joining a world-class team that combines deep research expertise and real-world product execution, with experience spanning Deepmind, Google, Amazon, Miro, Elise AI, IBM and Accern.
Position Summary
You'll lead the product team defining what an "agent" actually is. This means owning the core AI workforce product: execution, process automation, communication, and skills/training. This role combines hands-on product development with thought leadership on agentic AI while shipping to enterprises with 50k+ employees.
You'll own the AI Workforce product stream including agent execution, workflows, communication, and skills & university (training/maturation). You'll define product strategy and roadmap for the core agentic system, establish the definition of "what is an agent" for the company and industry, and lead Skills & University where we train models, optimize prompts, and mature agents with organizational context. You should be able to explain to the CEO and CTPO what an agent really means.
Responsibilities
Lead product for 4 teams: execution, process automation, communication, skills & university
Spend significant time in skills & university, the core innovation area for agent training and maturation
Define agent architecture: Is a process an agent? Is an agent a human replacement? These are nuanced questions you'll answer.
Ship features that work for enterprises, not just demos for engineers
Work closely with your engineering counterpart to balance innovation and execution
Participate in EPD leadership and shape overall product direction
Build credibility as someone who can write or speak authoritatively on agentic AI
Ship agent training and maturation system (skills & university) to production in first 12 months
Define and document "what is an agent" framework adopted across the company
Lead 3+ enterprise customer implementations and iterate product based on feedback
Publish or present thought leadership on agentic AI externally
Reduce ambiguity in agent architecture so engineers know what they're building
Key Qualifications
Director-level Product Manager or Group Product Manager
Hands-on experience building agentic AI systems (non-negotiable)
ML/AI product background required with substantial depth in the field
Experience with LLM training, prompt optimization, or agent frameworks (n8n, CrewAI, Sierra, etc.)
Enterprise product sense: you understand org processes, compliance, separation of concerns
Ability to go deep technically and explain agent architecture to engineers
Coming from product organizations, not engineering or research
Preferred Experience
Built vertical AI products serving enterprises
Worked on agentic systems that went to production, not just prototypes
Experience defining "what is an agent" at both the conceptual and implementation levels
Background in skills training systems or model maturation platforms
Personal Characteristics
Thought leader mindset with ability to influence industry direction
Hands-on approach, not just strategic oversight
Deep technical curiosity about agent architecture and capabilities
Strong communication skills for explaining complex concepts
Comfortable with ambiguity and defining new categories
Bias toward shipping and learning from production deployments