Linktree11 followers4 jobs

Staff Applied AI Engineer, AI Experiences & Agents

Mid levelSeniorFull-timeHybridMelbourne VIC, AustraliaPosted 3 months agoVerified 2 months ago
Pending fitX of Y criteria met

About the job

The Applied AI Engineer job at Linktree is all about transforming cutting-edge AI capabilities into impactful product experiences for creators and businesses. This position plays a crucial role in building AI agents and experiences that empower users to create, personalize, and automate their digital presence. The team thrives on collaboration across product, design, data, and engineering, fostering a dynamic environment where innovation and user feedback drive development.

Meet the team

About the company

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You'll be responsible for

🚀

Building and shipping AI experiences

Creating and delivering creator-facing and visitor-facing AI experiences from prototype to production.
🔧

Designing multi-agent workflows

Crafting workflows that integrate prompting, tool use, retrieval, memory/state, orchestration, and human-in-the-loop controls as needed.
📊

Creating evaluation suites

Developing regression harnesses and quality metrics to ensure AI quality improves systematically rather than by chance.

Key criteria

💻

Strong software engineering fundamentals

Proven experience shipping production systems end-to-end.

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🤖

Hands-on experience with AI products

Experience building LLM-powered products or similar AI experiences.

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📊

Experience building evals for AI quality

Demonstrated ability to create eval suites for AI output.

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A meaningful career starts with a match

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5 criteria for this job
Strong software engineering fundamentals
Proven experience shipping production systems end-to-end.

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Hands-on experience with AI products
Experience building LLM-powered products or similar AI experiences.

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Experience building evals for AI quality
Demonstrated ability to create eval suites for AI output.

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Strong product sense
Ability to identify user problems and simplify solutions.

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Good judgment on AI safety
Awareness of trust, privacy, and failure modes in AI systems.

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