Founding AI Engineer

Founding AI Engineer — Remote (LATAM) — Contract About Rad Hires Rad Hires is a recruiting partner that connects high-growth companies with exceptional talent. We work closely with our clients to understand what they actually need — not just what's written in a job posting — and we work closely with candidates to find roles that genuinely fit. About the Company Our client is a bootstrapped AI company operating in the GTM / marketing-tech space, generating roughly $1M in annual recurring revenue with tier-one clients — no outside funding, no burn-rate pressure, just a real business with real customers. Their product gathers public and private context on client executives and turns it into authentic, high-performing content strategies that help those clients win more business. They're now building out engineering capacity, starting with a founding hire in a new country who will help shape the team that follows. About the Role This is a founding engineering seat. You'll be the first engineer hired in your region, working directly with the founder, with real ownership over what gets built and how. The immediate need is delivery: shipping product work that isn't getting done today. The larger opportunity is helping establish and eventually grow an engineering team from the ground up. This is applied AI work in production — not research, not experimentation for its own sake. What You'll Do

• Design, build, test and ship production systems end-to-end, largely in TypeScript
• Build and maintain LLM-based workflows that power the core product — turning gathered context into content output
• Work on retrieval and related systems as the product's needs evolve
• Take ambiguous problems directly from the founder and figure out what to build, without a detailed spec
• Use AI tools in your own day-to-day engineering work
• Help lay the technical and cultural foundation for the engineering team that gets built around this hire

What We're Looking For

• Strong TypeScript and backend engineering skills — you can independently design, build, test and ship production systems
• Real production experience with LLMs — beyond simple API wrappers
• You use AI tools in your own day-to-day engineering work
• Comfortable operating without a detailed spec — you figure out what to build and why
• Minimum 1–2 years of relevant experience (flexible for the right person)
• Minimum 5–6 hours of daily overlap with UK time zone

Bonus Experience

• Agents and multi-step AI workflows — orchestration, state, retries, tool use, reliability
• RAG and retrieval — embeddings, vector search, hybrid search, reranking, chunking, retrieval evaluation
• Building evals — turning subjective requirements into datasets, metrics and repeatable experiments
• ML fundamentals — embeddings, ranking, classification, fine-tuning, preference learning
• Node.js and modern TypeScript frameworks; PostgreSQL and vector databases
• Knowledge graphs, recommendation/ranking systems, contextual bandits or RL, open-source models, multimodal AI, large-scale content or recommendation systems
• Experience in GTM, martech or content-tech products

Signals We Love

• You're a hands-on builder, not a process person — you'd rather ship than spec
• You care whether something actually improves the user's experience, not just whether the architecture is elegant
• You're genuinely interested in applied AI for go-to-market and content
• You're comfortable reading papers or technical writeups and translating the useful parts into production — you don't need to be an ML researcher

This Role Is Not For You If

• You need a detailed spec before you can start building
• You're coming from a large, process-heavy corporate engineering environment and thrive on structure over ambiguity

Logistics

• Location: Fully remote. Open to candidates in LATAM — time-zone fit matters more than geography
• Hours: Minimum 5–6 hours of overlap with UK working hours
• Engagement type: Contract — indefinite, ongoing engagement
• Compensation: Competitive monthly pay in USD
• Reports to: Founder, directly