[Remote] Founding Full-Stack AI Engineer

Note: The job is a remote job and is open to candidates in USA. Propel Labs is the research and development arm of Creative Design Group, building AI-native learning and development products for small and medium-sized businesses. The Founding Full-Stack AI Engineer will be the first engineering hire, owning architecture and end-to-end development across AI pipelines, SaaS and mobile applications, data, infrastructure, security, and deployment.

Responsibilities

• 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
• 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
• 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
• Month 1: Get deep in the existing codebase and product. Deliver an honest technical assessment: what to keep, what to rebuild, what will break at scale
• Months 2-3: Own and ship a significant feature end to end. Establish the evaluation harness for AI output quality
• Months 4-6: Harden the platform for real customers. Multi-tenant security, usage metering, monitoring, and a deploy process you trust on a Friday

Skills

• 2-3 years shipping production web applications, including at least one multi-tenant SaaS product you helped architect rather than inherited
• Strong TypeScript 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
• 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 non-deterministic output behave inside a system that has to be reliable
• You have built golden datasets and regression tests for LLM output, and you have opinions about where LLM-as-judge is useful and where it lies to you
• Cost and latency as first-class constraints: token budgeting, caching, streaming, model routing, knowing when the cheap model is sufficient
• Security in AI systems, specifically prompt injection through parsed documents and scraped web content, plus PII handling in prompts and logs
• Comfortable in Python for the AI and data layer
• You use AI coding tools aggressively and well. This is not a preference, it is how we operate. We expect you to ship at a pace that assumes them, and to know where they produce confidently wrong code that needs a human
• You can explain a technical tradeoff to a non-technical stakeholder without condescension or hand-waving
• You make good decisions with incomplete requirements, and you ask rather than guess when the stakes are high
• You care about the outcome for the end user, not just closing the ticket
• Degree in computer science or a related field, or equivalent practical experience. We care about what you have built
• EdTech, HR tech, or LMS experience, including standards like SCORM or xAPI
• Row-level security policy design at scale
• Event pipelines and analytics: turning behavioral data into something a customer will act on
• Early-stage or founding-engineer experience

Benefits

• Bonus
• Future equity participation opportunities
• Health insurance
• Dental insurance
• Vision insurance
• Life insurance
• 401(k) benefits

Company Overview