Head of Engineering (Lead Engineer)

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The Opportunity

We are seeking a deeply experienced and hands-on Head of Engineering (Lead Engineer) to serve as our core technical leader. This individual will own the architecture of our next-generation platform, guide our migration from existing systems, build early core services, and ultimately grow and lead the engineering team that will scale our AI-enabled venture studio platform to thousands of entrepreneurs worldwide.

You will be the principal architect of our multi-model AI platform and the technical owner of the Intelligence Stack across all layers—Frontend, Backend, and AI Orchestration.

This is a role for someone who wants to design the blueprint and build the foundation of a system that will shape the future of entrepreneurship.

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About Us

Builders + Backers has radically reimagined entrepreneurship. We operate the world's first AI-enabled venture studio for entrepreneurship education, combining conversational AI, data-driven behavioral insights, and proven venture creation methods. Our mission is to democratize access to entrepreneurial resources, creating a new onramp to entrepreneurship for everyday innovators—anyone, anywhere, anytime. AI-powered, expert-guided.

Key Responsibilities

Platform Architecture & Technical Leadership

• Design the end-to-end system architecture for our custom platform, including React/Next.js, Node/Python services, PostgreSQL, and vector databases.
• Architect the multi-model AI abstraction and orchestration layer, including model routing, provider integrations, and cost optimization strategies.
• Define API contracts, data schemas, integration patterns, and architectural standards across all platform layers.
• Lead the design of a multi-tenant, multi-model AI platform capable of serving thousands of users simultaneously and securely.
• Establish engineering best practices, technical health monitoring, observability, and reliability patterns.
• Oversee agency knowledge transfer and comprehensively document legacy system dependencies and constraints.
• Design migration paths and lead the transition from current systems to the new proprietary platform.

Core Platform Development

• Build the first core services, including the retrieval layer, APIs, workspace infrastructure, and system backbone.
• Implement data pipelines, storage strategies, and hybrid architectures supporting AI/ML capabilities.
• Integrate OpenAI, Anthropic, and other LLMs, designing intelligent routing, prompt pipelines, and model-selection frameworks.
• Own cloud infrastructure setup (AWS/GCP/Azure), including authentication, security, logging, and deployment pipelines.