Backed by Index and Insight.
About the role
The AI Agents and Experience team focused on turning frontier model capabilities into useful, trustworthy product experiences for creators, businesses, and their audiences. As an Applied AI Engineer at Linktree, you’ll work across product, design, data, and platform engineering to build AI agents and AI-powered experiences that help people create, personalize, automate, and grow from one Linktree.
What they're looking for
- Strong software engineering fundamentals and a track record of shipping production systems end-to-end
- Hands-on experience building LLM-powered products, agents, chat systems, RAG workflows, or similar AI experiences
- Experience building evals for AI output quality harnessing
- Strong product sense: you can identify the real user problem, simplify the solution, and make practical trade-offs around effort, scope, and quality
- Ability to frequently weigh trade-offs and understand the benefits of keeping systems architecture simple
- Good judgment on safety, trust, privacy, abuse, and failure modes in AI systems
More about this role
The AI Agents and Experience team focused on turning frontier model capabilities into useful, trustworthy product experiences for creators, businesses, and their audiences. As an Applied AI Engineer at Linktree, you’ll work across product, design, data, and platform engineering to build AI agents and AI-powered experiences that help people create, personalize, automate, and grow from one Linktree.
This role is for a strong product engineer who can move from concept to prototype to production. You’ll move quickly, learn from real usage, and harden what works with evaluation, observability, safeguards, and strong product judgment. This is not a pure research role. It is a build-and-ship role.
- Build and ship creator-facing and visitor-facing AI experiences end-to-end, from prototype through production.
- Design multi-agent workflows that combine prompting, tool use, retrieval, memory/state, orchestration, and human-in-the-loop controls where appropriate.
- Create eval suites, regression harnesses, and quality metrics so AI quality improves deliberately rather than by anecdote.
- Partner closely with product, design, data, and trust teams to translate ambiguous user problems into...
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