Head of Engineering

About Sapience AI

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share.

The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that.

Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves.

Let's achieve more, together.
Where this role sits

This is the senior-most engineering role at Sapience AI. You own the technology, the architecture, and the engineering organization that build the collective intelligence platform.

You are accountable for MINERVA and the COGENT architecture: how they are designed, how they scale, how they stay trustworthy, and how quickly the organization can ship. You set technical direction and build the team that delivers on it.

You sit on the executive team, translating company strategy into technical strategy and back, and making the calls that determine whether Sapience AI can build what it has promised.
Why this role exists

Collective intelligence at the scale of professional communities is a hard systems problem: reasoning over messy knowledge, earning trust, protecting sensitive data, and doing it reliably. Someone has to own whether the technology can actually deliver on the vision.

In an AI market moving this fast, the durable advantage is an engineering organization that learns and ships faster than the field, on an architecture that can carry the next several years.

The Head of Engineering supplies that. You own the technical strategy, the architecture, the team, and the standards, and you are accountable for turning ambition into a platform that works and holds trust.
What you will own (Areas of Responsibility)

You hold eight areas of responsibility across the engineering organization. Each one is yours to set direction on, build, and be accountable for.
1. Technical strategy and vision

• Own the technical strategy that turns company goals into a platform that can deliver them.
• Set a clear technical point of view on where AI is heading and how Sapience AI should build for it.
• Make the build, buy, and bet decisions that shape the next several years.

2. Architecture of MINERVA and COGENT

• Own the architecture of the MINERVA platform and the COGENT neuro-symbolic system, and how they scale.
• Ensure the architecture can carry growth, new communities, and rising demands on reasoning and trust.
• Balance near-term delivery against the durable foundations the platform needs.

3. Engineering organization and talent

• Build, structure, and lead the engineering organization, including hiring, leveling, and leadership development.
• Set the bar for engineering craft and hold it.
• Create an environment where strong engineers do the best work of their careers.

4. Delivery and execution

• Own how the organization plans, ships, and learns, and keep it fast without breaking trust.
• Drive delivery through GR and GA milestones with clear accountability.
• Remove the blockers that slow the whole organization down.

5. Trust, security, and reliability

• Own the security, privacy, and reliability of a platform holding sensitive community knowledge.
• Make trust a property of the architecture, not a review at the end.
• Be accountable for how the platform behaves when it matters most.

6. AI and research translation

• Partner with research and applied AI to turn frontier capability into dependable product behavior.
• Decide which advances are ready for production and which are not yet.
• Keep the organization honest about what AI can and cannot do.

7. Executive partnership and company strategy

• Serve on the executive team, and translate between company strategy and technical reality.
• Give the board and leadership a clear, honest view of technical risk and opportunity.
• Partner with product on what is possible, and by when.

8. Cost, scale, and operational excellence

• Own the economics of running the platform, including inference and infrastructure cost at scale.
• Build the operational discipline that keeps a growing platform reliable and affordable.
• Make scale a planned outcome, not a recurring emergency.

AI-augmented ways of working

You lead an organization that treats AI as part of how it builds. You set the standard for using AI to raise engineering velocity and quality, from code to review to operations, and you make sure judgment and accountability stay with people.

The standard is human in partnership: AI accelerates the work, you own the judgment, the interpretation, and the call. The people who create the most value here are not the ones producing the most output. They are the ones turning evidence into clear, durable decisions.
What this role is not

To keep the boundary clear:

• This is not a hands-off figurehead role. You own real technical direction and are accountable for what the organization ships.
• This is not a pure people-management role. You hold a technical point of view and make architecture-level calls.
• This is not a research-lab role. You are accountable for a platform in production, not open-ended exploration alone.
• This is not a product management role. You partner with product on what to build; you own how it is built and whether it works.

What success looks like

We measure this role on outcomes the team can see:

• A platform that delivers. MINERVA and COGENT scale, hold trust, and carry the company's ambitions.
• Velocity with trust. The organization ships fast without compromising security or reliability.
• A strong team. You attract, grow, and keep engineers who do their best work here.
• Sound economics. The platform runs reliably at a cost that scales with the business.
• Frontier, made dependable. Research and applied AI advances become production behavior members can rely on.
• Clear executive partnership. Leadership and the board have an honest view of technical risk and opportunity.

Who you are
Required qualifications

• Extensive engineering leadership experience, including leading and scaling engineering organizations.
• Deep technical background in large-scale systems, and hands-on credibility that engineers respect.
• Direct experience building and operating AI or ML systems in production.
• A track record of owning architecture that scaled with a growing business.
• Strong judgment on security, privacy, and reliability for sensitive data.
• Executive presence, and the ability to translate between business and technical strategy.
• A record of attracting, growing, and keeping strong engineers.

Preferred qualifications

• Experience with neuro-symbolic systems, knowledge graphs, retrieval, or agentic AI.
• Experience owning inference and infrastructure economics at scale.
• Experience in trust-sensitive or regulated domains.
• Familiarity with CRM, AMS, or knowledge-platform ecosystems.
• Experience as a technical co-founder or early engineering leader.

How you work

• You lead with the mission and name the real problem before the solution.
• You hold a clear technical point of view and defend it with evidence.
• You make hard calls and own the outcomes.
• You treat trust, security, and reliability as non-negotiable.
• You build teams where people do their best work and trust each other.
• You keep the organization learning and changing course without ego.

Skills & Competencies

• Technical strategy and architecture at platform scale.
• Building and scaling engineering organizations.
• Production AI and ML systems, including reliability and cost.
• Security, privacy, and governance for sensitive data.
• Delivery leadership and operational excellence.
• Executive communication and board-level partnership.
• Translating research and frontier capability into production.

Services & Tools Experience

• Modern cloud platforms (AWS, GCP, or Azure) and large-scale infrastructure.
• Distributed systems, data platforms, and ML infrastructure.
• LLM, retrieval, vector, and graph systems at an architectural level.
• Observability, security, and reliability tooling.
• Engineering delivery and planning systems.
• Cost and capacity management for AI workloads.
• Deep familiarity with the MINERVA platform and COGENT architecture (as the accountable owner).

Prior Experience & Background

• Prior senior engineering leadership (VP Engineering, CTO, or equivalent) at a software or AI company.
• Experience scaling both an architecture and an organization through growth.
• A track record of shipping and operating AI systems in production.
• Experience partnering at the executive and board level.

Cross-functional partners

You partner most closely with the CEO and executive team, Product, Research, Applied AI, and Security. You lead the engineering organization and are accountable for how MINERVA and COGENT are built, scaled, and trusted.
How we hire

We review every application, and we encourage you to apply even if you do not match every line above. Research shows that talented people, especially those from underrepresented communities, often hold back when they do not meet every qualification. If that is the only thing holding you back, apply anyway.

Sapience AI is an equal opportunity employer. We are committed to a workplace where everyone, regardless of background, has a voice in building what comes next.
Compensation

Base Salary: $228,000 - $240,000 + early stage equity

Generous health and wellness benefits

Sapience AI is an equal opportunity employer. We do not discriminate on the basis of gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. If you need an accommodation to complete our application process, let your recruiter know.