Vice President of Engineering

The Mission Build the engineering organization and technical foundation that will allow enterprises to run their most critical workflows through AI agents they can trust.

Factify is building the truth infrastructure for enterprise AI. We transform fragmented policies, documents, decisions, and data into governed organizational truth, then ensure that AI agents operate according to it.

As our VP R&D, you will lead the team responsible for turning that vision into a category-defining enterprise platform. This is not a pure people-management role. It is also not a chief architect role disguised as management. We are looking for a rare combination: a deeply technical engineering leader who can shape architecture and challenge the strongest engineers in the room, while building an organization in which talented people grow, collaborate, make independent decisions, and take full ownership of outcomes.

What You Will OwnSet the technical direction • Partner with the CEO, Product, and company leadership to define the technical strategy behind Factify’s platform.

• Translate an ambitious product vision into clear architectural principles, technical priorities, and investment decisions.

• Make pragmatic tradeoffs between speed, simplicity, reliability, and long-term scale without allowing short-term execution to create an unmanageable technical foundation.

• Maintain enough technical depth to lead architecture reviews, challenge assumptions, identify hidden risks, and help the team solve its hardest problems.

Build an enterprise-grade agentic platform Lead the development of systems that enable AI agents to operate safely and reliably inside complex enterprises.

This includes areas such as:

• Agent orchestration, planning, tool use, and execution

• Governed knowledge and policy representation

• Retrieval, context construction, and memory

• Model and workflow evaluations

• Human review and escalation mechanisms

• Permissions, identity, security, and auditability

• Reliability, observability, and incident response

• Cost, latency, and model performance optimization

• Enterprise integrations and production deployment

•

You do not need to be the expert in every domain. You must understand these systems deeply enough to set direction, hire the right experts, ask difficult questions, and recognize the difference between a compelling demonstration and a dependable production system.

Build and lead the R&D organization • Design the organizational structure required for the next stage of the company.

• Recruit exceptional engineers and engineering leaders while maintaining a high and consistent hiring bar.

• Develop managers and senior individual contributors who can lead important technical and organizational domains independently.

• Create clear expectations, career paths, feedback mechanisms, and performance standards.

• Address performance issues directly and fairly. Recognize exceptional work. Give people the context and support required to grow beyond their current capabilities.

• Build a leadership bench that prevents the organization from depending on a small number of people for every important decision.

Create autonomy with accountability • Build an environment where engineers have real ownership rather than waiting for instructions.

• Define clear outcomes, decision boundaries, technical standards, and interfaces between teams. Then allow decisions to be made as close as possible to the problem.

• Encourage independent judgment without creating disconnected teams or inconsistent architecture.

• Ensure that autonomy produces better decisions and faster execution, not ambiguity, duplicated work, or avoidance of responsibility.

• Create a culture where people share context openly, challenge one another constructively, ask for help early, and remain accountable for results from design through production.

Raise engineering velocity and quality together • Establish an operating model that allows the company to move quickly without normalizing instability or technical shortcuts.

• Improve planning, prioritization, development workflows, testing, deployment, observability, and incident learning.

• Introduce useful engineering metrics without turning the organization into a reporting machine.

• Use AI-native development practices to increase the leverage of every engineer, while maintaining clear standards for security, correctness, maintainability, and human judgment.

• Identify recurring sources of friction and replace them with better infrastructure, tools, abstractions, and working methods.

Connect engineering to customers and the business • Work closely with Product to shape the roadmap rather than only receiving requirements.

• Partner with customer-facing teams to understand how major enterprises evaluate, deploy, secure, and govern AI systems.

• Participate in strategic customer conversations when technical leadership can accelerate learning, build trust, or unblock adoption.

• Translate business context into engineering priorities and technical decisions into clear business implications.

• Operate as a company leader, not only as the leader of one function.

What We Are Looking For • Significant experience building complex software systems, with deep technical foundations in backend systems, cloud infrastructure, distributed systems, data platforms, or enterprise architecture.

• Several years of experience leading engineering organizations through managers, senior technical leaders, and multiple teams.

• A track record of scaling an engineering organization while preserving technical quality, speed, accountability, and a strong talent bar.

• Meaningful experience building or operating AI, machine learning, agentic, or LLM-based systems in production.

• A strong understanding of the technical challenges behind reliable AI agents, including evaluations, orchestration, context, model behavior, observability, permissions, security, and failure handling.

• The ability to contribute credibly to architecture and technical strategy without becoming the approval bottleneck for every decision.

• Evidence that you treat management as a craft, including hiring, coaching, feedback, performance management, organizational design, and leadership development.

• Experience creating teams that operate with high autonomy while remaining aligned around shared architecture, priorities, and outcomes.

• Strong product and business judgment. You understand that excellent engineering is measured by the problems it solves, not only by the sophistication of the technology.

• Clear and direct communication with engineers, executives, customers, and non-technical stakeholders.

• Comfort operating in an early-stage environment where the product, organization, and category are still being shaped.

• High standards without ego. You can change your mind when the evidence changes and create room for other people to lead.

Particularly Relevant Experience Experience in one or more of the following areas would be valuable:

• Enterprise AI or agentic platforms

• Regulated or high-stakes enterprise software

• Developer platforms or infrastructure products

• Knowledge systems, policy engines, or workflow orchestration

• Security, identity, authorization, or compliance infrastructure

• Building an engineering organization through a major stage of company growth

• Working directly with large enterprise customers

• Previous experience as a founder, CTO, VP Engineering, VP R&D, or senior engineering director

What Success Looks Like During your first year, you will have:

• Established a clear technical strategy and architecture for the next stage of Factify’s platform.

• Built an R&D structure with clear ownership, strong leaders, and fewer organizational dependencies.

• Improved the speed and predictability with which the company turns product priorities into production capabilities.

• Raised the standard for reliability, security, evaluations, observability, and operational ownership.

• Recruited and developed exceptional engineering talent.

• Created an environment where teams make strong independent decisions without losing alignment.

• Made AI a meaningful source of engineering leverage across the organization.

• Built a trusted partnership between R&D, Product, customers, and the rest of the company.

• Increased the organization’s ability to solve difficult problems without requiring your direct involvement in each one.

How We Think About Leadership Leadership is not control.

Your responsibility is to create clarity, develop judgment, raise standards, and build a system in which other people can succeed.

The strongest engineering organization is not the one in which every decision reaches the VP. It is the one in which people understand the mission, have the context required to act, know what excellence looks like, and take responsibility for the consequences of their decisions.

We are looking for someone who believes deeply in the power of a group, invests seriously in individuals, and knows how to turn exceptional engineers into an exceptional organization.