Founding Full-Stack AI Engineer

We’re Propel Labs, the new research and development arm of leading learning and development agency Creative Design Group. Our award-winning agency designs cutting-edge learning and development solutions for Fortune 500 companies. Join us as we look to build the future of learning and development solutions!

We are building AI-native learning and development products for small and medium sized businesses. Beyond that, we keep the details close, and we will walk you through the products, the architecture, and the roadmap in detail once we are talking. What we can tell you now: there is a working product, real technical depth to the problem, and no engineering team yet.

You are the first engineering hire. You will write the majority of the code, make most of the architecture calls, and own the product end to end: data model, backend, AI pipeline, web app, mobile app, and deploys.

This is a hands-on individual contributor role, not a management role. You will work directly with the Director of Product & AI Strategy on scope and priorities, and with our instructional design and creative teams on product functionality and features. As Propel Labs grows, there is a clear path into technical leadership, but that is earned by shipping value, not granted on day one.

Be honest with yourself about whether you want this. Founding engineer work means ambiguity, unglamorous plumbing, and a lot of decisions made with incomplete information. It also means the architecture is yours.

• The AI layer:
  Generation and synthesis pipelines built on frontier models, retrieval over customer-supplied documents, and the evaluation harness that keeps output quality from regressing every time we change a prompt. This is applied LLM engineering. We build on foundation models; we do not train them.
• The product surface: A multi-tenant SaaS web application plus a mobile app, along with internal authoring tools and customer-facing admin and reporting views.
• The platform underneath:
  Data model and tenant isolation, authentication and role-based access, background job processing for long-running generation work, usage metering (AI costs scale with usage, so this matters commercially), billing, and CI/CD.
• Ingestion:
  Document parsing across PDF, DOCX, and slides, plus web research to enrich generated output. Both pull in untrusted content, so both need to be handled defensively.

• 2-3 years shipping production web applications, including at least one multi-tenant SaaS product you helped architect rather than inherited.
• Strong Type Script and Python. Strong React experience - complex state, data fetching and caching, and keeping a large single-page app fast and maintainable.
• Relational data modeling in Postgres: schema design, migrations, indexing, query performance. You can explain how you would enforce tenant isolation and why you chose that approach.
• Mobile delivery experience, ideally React Native or Expo, including the parts people underestimate (builds, store review, OTA updates, offline state).
• Async and background processing: queues, workers, webhooks, retries, idempotency. Generation jobs take minutes, not milliseconds.
• Cloud infrastructure and operations: containers, environments, secrets management, observability, CI/CD. You have been on call for something you built.
• You have built and shipped a production RAG system, not a demo. You can talk specifically about chunking strategy, embedding model choice, hybrid search versus pure vector search, reranking, and how you measured whether retrieval was actually working.
• Prompt and context engineering as an engineering discipline: structured outputs, tool and function calling, multi-step orchestration, managing context windows, and making…