Chief Intelligence Architect
About the role
Lumenfolk is seeking a Chief Intelligence Architect to help architect, evaluate, and continuously improve the AI and knowledge systems powering CanonIQ, Brain Console, and future Lumenfolk products. This role is not a prompt engineering role, a traditional enterprise IT role, a pure academic ML research role, a generic full-stack engineering role, a chatbot builder role, or a vendor management role with no technical depth. It is a founder-track architecture role for someone who can think deeply about LLM systems, knowledge architecture, retrieval, evaluation, governance, product intelligence, and long-term technical defensibility.
Responsibilities
AI Systems Architecture: Design the technical architecture for Lumenfolk's AI-powered products. Define how models, tools, agents, workflows, retrieval systems, and user interfaces work together. Make decisions about model selection, model routing, context windows, orchestration, cost, latency, and reliability. Help determine when to use RAG, long-context models, fine-tuning, structured workflows, deterministic logic, or human review. Create scalable architecture patterns that can support multiple Lumenfolk products.
Knowledge Architecture: Design the knowledge structure behind CanonIQ and related products. Develop taxonomies, schemas, metadata standards, memory models, and source hierarchies. Improve retrieval precision, citation quality, and context relevance. Help define how knowledge enters, changes, expires, gets verified, and becomes usable by AI systems. Build systems that distinguish raw source material, working ideas, canonical knowledge, product runtime guidance, and user-specific context.
LLM Evaluation and Quality: Create evaluation frameworks for AI product behavior. Define benchmarks for accuracy, usefulness, groundedness, retrieval quality, hallucination reduction, and task completion. Build regression testing processes so the system improves without breaking prior capabilities. Establish release-readiness standards for AI behavior. Translate vague product quality concerns into measurable evals.
CanonIQ Product Intelligence: Help shape CanonIQ from concept into a durable intelligence product. Partner with the founder on product strategy, technical feasibility, user experience, and differentiation. Identify where intelligence should be automated, governed, surfaced, constrained, or handed back to humans. Help turn founder insight, market learning, product usage, and organizational knowledge into product architecture.
AI Governance and Trust: Design systems that support transparency, source traceability, permissions, review gates, and appropriate human oversight. Partner on trust, compliance, privacy, and explainability requirements. Ensure Lumenfolk's products are not just impressive, but dependable.
Technical Leadership: Help define the early technical roadmap. Support hiring and evaluation of engineers, contractors, vendors, and AI implementation partners. Review technical work for architectural quality. Translate between founder vision, product requirements, and technical execution. Build the operating discipline needed for an AI-native company to improve over time.
Qualifications
Experience with LLM application architecture, AI systems design, retrieval-Augmented Generation, vector databases and embeddings, knowledge graphs, ontologies, taxonomies, semantic systems, evaluation frameworks for LLM products, agentic workflows and tool orchestration, AI product development, data architecture or information architecture, model selection, model routing, and AI infrastructure decisions.
Ability to build early-stage technical systems from ambiguity.
Background in roles such as Principal AI Architect, AI Systems Architect, LLM Architect, Staff or Principal Applied AI Engineer, AI Platform Architect, Knowledge Architect, Founding AI Engineer, Technical Product Architect, CTO / technical co-founder of an AI-native product.
Skills
Deep understanding of LLM systems, knowledge architecture, retrieval, evaluation, governance, and long-term technical defensibility.
Strategic judgment and the ability to challenge, sharpen, and extend the founder's thinking.
Technical depth and architectural taste.
The courage to help build something ambitious from first principles.
Benefits
This is an early-stage, founder-track opportunity. The company is not yet structured for a traditional market-rate executive salary from day one. Compensation is expected to be built around a combination of meaningful equity, milestone-based compensation, possible consulting or fractional compensation during an initial trial period, and future salary as financing, revenue, or company stage supports it.
Pay
Compensation structure is not specified, but it is expected to be built around a combination of meaningful equity, milestone-based compensation, possible consulting or fractional compensation during an initial trial period, and future salary as financing, revenue, or company stage supports it.
Schedule
The schedule is remote / flexible.