AI Engineer

Awesome Motive · Brazil

RemotoTempo integral

Publicada há 2 horas

Sobre a vaga

As an AI Engineer, you're responsible for designing, building, and shipping AI systems that real people use, from AI features inside products used on over 30 million websites to internal tools built on our behavioral and operational data. You will turn messy real-world data and a user's goals into output people can trust and act on: generated campaigns and content, plain-English recommendations, and automations that save hours of work. We hire for caliber first, then match you to the team where you will have the most impact.

Interested in applying?

Please read/follow the next steps outlined in "How to Apply" at the bottom of this listing.

Attention to detail is one of our core values! This is your chance to stand out :)

To love this role, here's the type of person you are:

  • You're a builder at heart. You don't just use AI tools, you understand how they work under the hood, and you think about how to make them useful for real people, not just technically impressive.
  • You care more about how good the output is than which model produced it, and you get restless when an AI feature is just fine.
  • You're a self-starter who can take a loosely defined problem, figure out the right approach, and ship a working solution without needing to be told what to do next.
  • You think about the user and the decision first, not the pipeline and the model. When you see data, your first instinct is to ask what question it answers for the person who needs it.
  • You're comfortable owning the full stack of an AI project, from data exploration and model selection to the API, the interface, and deployment, and making sure it actually works in production.
  • You build with AI every day, and you still verify everything before it ships. "The AI did it" is never your answer.
  • You're an excellent communicator, fluent in both verbal and written English. You can explain complex technical decisions to non-technical stakeholders without dumbing it down.
  • You take pride in the quality and craftsmanship of your work: clean code, proper error handling, thoughtful architecture, not just something that works on the happy path.
  • You have the curiosity and desire to learn and grow. The AI landscape moves fast and you keep up because you genuinely enjoy it, and you share what you learn so the people around you get faster too.
  • You're a team player who is comfortable working alongside developers, product, design, and marketing, and doesn't take critical feedback personally.

Common responsibilities include (but are not limited to):

  • Designing and shipping AI features that turn a user's goal, website, or data into campaigns, content, and recommendations they can act on.
  • Building AI-powered internal tools and data-driven systems used across the organization: analytics platforms, reporting automation, and workflow intelligence.
  • Designing and building LLM pipelines with solid prompt design, structured and validated output, RAG, guardrails, and agentic workflows.
  • Cleaning and analyzing messy product and behavioral data, and grounding AI output in the facts so it never makes numbers up.
  • Building data pipelines that ingest, transform, and serve behavioral and operational data at scale.
  • Setting up evaluation and observability so every iteration is measurably better than the last, and failures are caught before users see them.
  • Owning the full path from model output to what the user sees, across backend and frontend.
  • Evaluating and selecting the right models, frameworks, and infrastructure for each use case, balancing quality, cost, and latency.
  • Watching how people actually use what you build, and turning that into the next improvement.
  • Writing clean, well-tested, production-grade code with proper error handling, logging, and observability.
  • Documenting your work, including how you used AI to build it, so others can learn from it and reuse it.
  • Keeping up with the rapidly evolving AI landscape and bringing new ideas, tools, and approaches to the team.
  • Communicating with the team and supporting your peers using chat, audio, and video.

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