Head of Engineering, Organization & Governance
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 will lead the product engineering stream building the governance foundation for a new hybrid workforce in global enterprises. The system models organizations around goals, actors, their roles, actions, assets and policies. It serves as a control plane for organizational execution and compliance, providing both back-office admin interface as well as insights for company leadership. This is the critical infrastructure that enables holistic view on enterprise companies to help with rolling up their processes at scale.
Responsibilities
Build and scale a 5 to 30+ person engineering organization across European time zones (including UK and IL)
Partner with product management to define and deliver roadmap
Contribute to the overall product engineering leadership
Drive engineering productivity across your teams
Define and automate SDLC, leveraging modern approaches and tools
Own culture and communication within your teams
Key Qualifications
Experience building engineering organizations from the ground up — hiring, scaling and leading engineering orgs of 30+ people across multiple teams, over multiple years, in EMEA (EU/UK/IL).
Director-level experience with strong process and people management skills
Proven experience building (not just maintaining) complex systems at scale
Comfortable with high ownership and ambiguity in a fast-moving startup environment
Familiar with security, compliance, and enterprise requirements
Excited about using agents and automation
15+ years engineering experience with credibility across senior stakeholders
Preferred Experience
Background at companies managing scale with tooling and agents
ML/AI background, and/or prior experience managing ML engineers
Experience serving enterprise customers
Personal Characteristics
Strong operator with execution focus, not purely visionary
High ownership and bias toward action
Ability to build, inspire, and motivate teams
Process-oriented with clarity in communication
Excited about leveraging AI, agents to improve code and automate eng operations
Strategic thinker who can balance immediate delivery with long-term architecture
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 will lead the product engineering stream building the governance foundation for a new hybrid workforce in global enterprises. The system models organizations around goals, actors, their roles, actions, assets and policies. It serves as a control plane for organizational execution and compliance, providing both back-office admin interface as well as insights for company leadership. This is the critical infrastructure that enables holistic view on enterprise companies to help with rolling up their processes at scale.
Responsibilities
Build and scale a 5 to 30+ person engineering organization across European time zones (including UK and IL)
Partner with product management to define and deliver roadmap
Contribute to the overall product engineering leadership
Drive engineering productivity across your teams
Define and automate SDLC, leveraging modern approaches and tools
Own culture and communication within your teams
Key Qualifications
Experience building engineering organizations from the ground up — hiring, scaling and leading engineering orgs of 30+ people across multiple teams, over multiple years, in EMEA (EU/UK/IL).
Director-level experience with strong process and people management skills
Proven experience building (not just maintaining) complex systems at scale
Comfortable with high ownership and ambiguity in a fast-moving startup environment
Familiar with security, compliance, and enterprise requirements
Excited about using agents and automation
15+ years engineering experience with credibility across senior stakeholders
Preferred Experience
Background at companies managing scale with tooling and agents
ML/AI background, and/or prior experience managing ML engineers
Experience serving enterprise customers
Personal Characteristics
Strong operator with execution focus, not purely visionary
High ownership and bias toward action
Ability to build, inspire, and motivate teams
Process-oriented with clarity in communication
Excited about leveraging AI, agents to improve code and automate eng operations
Strategic thinker who can balance immediate delivery with long-term architecture