Brazil onlyAbout the company:CloudWalk is a fintech company reimagining the future of financial services. We are building intelligent infrastructure powered by AI, blockchain, and thoughtful design. Our products serve millions of entrepreneurs across Brazil and the US every day, helping them grow with tools that are fast, fair, and built for how business actually works. Learn more at cloudwalk.io.
About the team:We are a small team within CloudWalk’s larger R&D effort, focused on bold ideas and new product directions. Our mission is to explore new concepts early, build fast, and uncover what is worth turning into real products. Sometimes that means prototyping features for existing experiences; other times, it means testing entirely new directions that could shape the future.We believe that large language models (LLMs) and autonomous agents will fundamentally transform how we interact with apps - shifting away from rigid screens and buttons, toward dynamic, context-aware experiences driven by intent and conversation.
Your role:You will explore how intelligent systems like LLMs and agents can unlock entirely new ways of interacting with mobile apps. You will design and build prototypes that move beyond static screens - creating interfaces that adapt, respond, and even initiate based on user intent, context, and autonomy.You will be part of an exploratory, collaborative environment - joining open-ended discussions, questioning assumptions, and helping set new directions as a team. Together, we rethink what is possible, test ideas quickly, and learn through building.
This role is perfect for someone who thrives in ambiguity, moves quickly from concept to code, and sees the interface itself as a medium for exploration. If you are excited about reshaping the future of mobile around language, intelligence, and interaction - we would love to meet you.
You will:Design and build mobile prototypes that explore new interaction models - from dynamic interfaces to agent-driven flows and voice-based navigation.Collaborate with ML engineers to integrate LLMs, agents, and real-time data into mobile experiences.Push the limits of what mobile apps can be - experimenting with novel UI patterns, input methods, and intelligent behaviors.This role combines strong mobile engineering skills with a deep curiosity for AI-powered interfaces, and is ideal for someone eager to turn emerging technologies into exploratory mobile experiences.
What we expect:Our projects often start with ambiguity and evolve rapidly - so we look for people who are deeply curious, adaptable, and driven by the desire to make ideas real.
Required skills:
- Mobile Prototyping: Proficiency in rapidly building and iterating on mobile interfaces using Flutter. You are comfortable sketching out flows, managing state, and stitching together UI logic to turn abstract concepts into usable interactions.
- Audio Capture & Interaction Handling: Hands-on experience with microphone access, audio session control, and real-time voice input on mobile. You can implement voice-triggered behaviors, handle streaming audio, and respond to interruptions like background noise or user silence.
- LLM Integration: Ability to integrate large language model (LLM) outputs into mobile UIs. You know how to design for model uncertainty, gracefully handling latency, retries, or incomplete outputs in the user experience.
- Interface Orchestration & State Management: Strong experience with state management tools to coordinate dynamic, responsive interfaces. You ensure the UI stays coherent as it reacts to asynchronous data, streaming input, or autonomous system behavior.
- Experimental Engineering Mindset: You thrive in low-structure environments, prototype quickly, and treat code as a tool for learning.
Nice-to-have skills:
- Conversational UI Experience: Exposure to designing or implementing interfaces where voice, intent, or agent-driven flows replace traditional touch interactions.
- Edge & Performance Awareness: Understanding of mobile performance constraints - latency, memory, battery - and how to optimize real-time or streaming interactions for responsiveness on-device.
- Basic ML or Audio Fluency: Familiarity with ML-powered APIs or common audio processing concepts
Recruiting process outline:
- Take-home challenge: This is a short exercise designed to showcase your technical skills, development process, and problem-solving approach.
- Technical interview: This in-depth discussion will assess your technical knowledge, problem-solving skills, and experience relevant to the role.
- Cultural interview: We will explore your work style, values, and how you might contribute to and thrive within our team culture.
Our process is designed to help us understand how you think, build, and collaborate. If you have a relevant GitHub repository, portfolio, or past project that reflects your work and interests, please share the link when you apply.
