Full stack AI Engneeir - AI Acquisition

 Posted 2 hours ago
  
 Worldwide
  
5-10 years experience
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AI Summary

Own product areas end-to-end, designing and implementing both the polished Next.js frontend and the underlying AI agent orchestration. Build and maintain core infrastructure and evaluation harnesses to ensure reliable agent behavior.

Senior Full-Stack Engineer — AI Engineer
AI Acquisition | Remote

About the role

AI Acquisition builds the AI agent platform that powers growth and revenue operations for thousands of businesses — from AI SDRs and LinkedIn outreach agents to autonomous account management and content generation. We're looking for a senior full-stack engineer who can operate as a de facto AI architect: someone who's just as comfortable shipping a polished Next.js interface as they are designing the agentic workflows and model orchestration running underneath it.

This is a high-ownership role for someone who's built things solo, moved at startup speed, and thinks in systems rather than tickets.

What you'll do

You'll own product areas end-to-end — architecture, implementation, and iteration — across our agent platform. That means building and maintaining core application infrastructure in React, Next.js, TypeScript, Node, and PostgreSQL, while also designing the AI layer that makes our agents actually work: multi-model orchestration, RAG pipelines and vector databases, semantic memory, prompt caching strategies, and token usage tracking. You'll build and maintain eval and testing harnesses to keep agent behavior reliable as models and prompts evolve, and you'll work closely with the founding team to translate fuzzy product ideas into shipped, working systems.

What we're looking for

  • Strong senior full-stack experience with real depth in React, Next.js, TypeScript, Node, and PostgreSQL — not just familiarity, but the ability to make sound architectural calls under ambiguity.

  • Hands-on experience building production AI systems: agentic workflows, multi-model orchestration, RAG/vector databases, prompt caching, semantic memory, token tracking, and eval/testing frameworks.

  • A track record of owning a product area solo or near-solo — whether that's a startup, a side project that went somewhere, or being the de facto AI architect on a small team.

  • Strong systems thinking and adaptable problem-solving; you can reason about tradeoffs across the stack, not just within your usual lane.

  • Clear, direct communication — you ask good questions, explain your thinking step by step, and aren't precious about being right.

  • An AI-native development mindset: you're already building with AI tools, not just bolting AI features onto existing products.

  • Genuine excitement about async, distributed work and a small, fast-moving team.

What stands out to us

We're filtering for substance over polish. The strongest candidates tend to have shipped something real on their own — a product, an internal tool, an agent system — and can talk through the decisions they made and why, without ego or defensiveness when challenged. If you're the kind of engineer who gets energized by ambiguity rather than needing it removed for you, this role is built for people like you.

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