We’re not here to waste your time. Read this carefully and only apply if you’re ready to do real work that matters.
What the job entails:
You’ll be part of a team that will design and implement the backend and intelligence layer of our AI-managed merchant network. This isn’t a forum plugin or a skin on top of a chat app. We’re designing a social fabric from scratch: matching merchants based on complementary offerings, shared pain points, and potential collaborations, then giving them the tools to grow together.,
Your main tasks:
Architect and build a system to ingest merchant data (business category, geography, scale, needs).Create agent-driven match-making and recommendation pipelines.Develop moderation agents that guide discussions, keep quality high, and eliminate noise or abuse.Integrate LLMs to facilitate onboarding, message summarization, semantic clustering, and auto-responses.Build and evolve internal protocols for autonomous agent behavior, governance, and feedback loops.Collaborate with frontend teams to create seamless user interactions with underlying intelligence.Ship prototypes quickly, iterate based on feedback, and move toward scalable systems.,
Technologies / techniques used:
Python (mandatory)LLM ecosystems (OpenAI, Anthropic, open models)LangChain, LangGraph or custom orchestration frameworksVector databases (Weaviate, Pinecone, PGVector)NLP and recommendation techniques (semantic search, user embeddings, graph-based recs)Moderation tooling (toxicity filters, content classifiers)GCP (preferred), Docker, CI/CD pipelines,
What you'll do:
Design, build, and maintain scalable and reliable artificial inteligence infrastructure.Deploy and monitor AI systems for real-time inference.Develop and maintain robust REST APIs for our AI services.Write clean, maintainable, and well-tested production code.Optimize and improve the performance of our AI systems.Stay up-to-date with the latest technologies and best practices in machine learning and AIOps.,
What you'll need:
Experience building real-time or asynchronous communication systems.Strong Python engineering skills and ability to deploy scalable services.Experience integrating LLMs into production environments.Understanding of graph-based systems, user recommendation, or matchmaking logic.Comfort building autonomous agents that act with minimal oversight.Portuguese and English fluency. This system will handle data from and interact with Brazilian merchants daily.Solid collaboration and product instincts. You can shape from zero with ambiguous specs.,
Nice to have:
Experience with social network dynamics, either through product work or research.Familiarity with community moderation tools, filters, or governance frameworks.Prior work on user embeddings or behavior-based clustering.Full-stack experience – you won’t build UI, but understanding it helps.Previous experience or openness to learn Elixir,
Recruiting process outline:
Technical case – explore a dataset of merchants and propose an intelligent recommendation approach.Interview – discuss architecture, agent design, and AI deployment experience.Cultural interview – alignment on autonomy, speed, and expectations.If you are not willing to work on a test case, do not apply.Diversity and inclusion:
We believe in social inclusion, respect, and appreciation of all people. We promote a welcoming work environment, where each CloudWalker can be authentic, regardless of gender, ethnicity, race, religion, sexuality, mobility, disability, or education.
