INFLEET is Brazil's first intelligent copilot for fleet management. Our mission is to connect data from telematics, video, and logistics systems to deliver insights that reduce accidents, optimize costs, and increase our clients' sustainability.
We are growing at least 100% year over year, expanding into Enterprise accounts, and going deep into new verticals: video telematics, fintech (INFLEET Pay), custom hardware, and AI-native operations. The engineering work that gets us to the next stage is not the same engineering work that got us here, and it is not the same engineering work most companies are still hiring for.
We are looking for Software Engineers who want to do the best engineering work of their career in the AI era: as orchestrators of AI under the guidance of strong senior engineers, building real production systems and developing the judgment that turns AI from a novelty into a serious engineering tool. If you are early-to-mid career, hungry, AI-fluent, and obsessed with becoming an excellent engineer (not just a fast one), this is for you.
Intensity to win. We believe extraordinary results are born from relentless focus, resilience, and a deep-seated passion for overcoming challenges. This intensity fuels our commitment to excellence and ensures we never settle for "good enough".
Partnership that creates value. We understand that sustainable success is never built in isolation. We thrive by creating win-win relationships, aligning our goals with our clients and colleagues to build mutual, lasting growth. Our success is measured by the success we create for others.
Autonomy that learns. We believe that innovation and agility come from empowerment. We trust our teams to take initiative and make decisions, knowing that every outcome, whether a success or a challenge, is a crucial opportunity to learn, adapt, and grow smarter.
We no longer believe code should be written the traditional way.
Inside INFLEET, AI generates the code. Engineers review, decide, refine, take responsibility, and ship. The value an engineer brings is no longer in how fast they type or how many lines they produce by hand. It is in judgment: knowing what to build, what to discard, what to question, what to refactor, what to test deeply, what to monitor, and what is safe to defer.
This is not a hobby for us, and it is not a "nice to have" in the description. It is the operating model. If you do not actively use AI tools (Claude Code, Cursor, Copilot, Codex CLI, or similar) in your day-to-day engineering work, this role will be uncomfortable. If you do use them, but treat them as autocomplete, this role will also be uncomfortable. We are looking for engineers who treat AI as a powerful, fallible collaborator and who are personally accountable for every line that makes it into main, regardless of who or what produced it.
To be explicit about what we are not looking for: engineers who paste large AI-generated diffs they did not read; engineers who copy code without understanding what it does or why; engineers who outsource judgment to the model; engineers who confuse output volume with progress. Vibe coding is the opposite of what we want.
The engineers we want are AI-fluent and even more demanding about the fundamentals because of it: maintainability, scalability, observability, API design, testability, performance, and a clear-eyed understanding of the business.
As a Software Engineer at INFLEET, your mission is to ship great features inside a squad, learn how production systems actually behave, and build the judgment that turns you into a senior engineer who can be trusted with critical systems.
You will work in a squad with a clear product area (it could be Telemetry, Transactions, OPS, Hardware, Payments, or whichever domain best fits your background and our roadmap, which we define together during the interview process), and you will own meaningful pieces of work end to end inside that domain. Your scope is intentionally smaller than a Senior's, and your code review will be deeper. That is the deal: you trade scope for support while you develop the judgment that lets you take on more.
You will be paired with senior engineers and tech leads who will mentor you, review your work carefully, and challenge your decisions. Mentorship at INFLEET is not the headline (you are not coming here to be taught from zero), but it is real, and it is part of how we accelerate good engineers into great ones.
Fully remote, with 4 on-site gatherings per year in São Paulo.
Own features end to end inside your squad. You take a problem from definition to production: design, implementation, tests, observability, deploy. You don't wait for a Jira ticket to tell you what to do next.
Orchestrate AI tools to produce production-grade code. You use Claude Code, Cursor, Copilot, Codex CLI, and the modern toolchain every day. You plan before you generate, you read every diff, you write the tests that matter, you reject what does not meet the bar, and you defend every line in code review as if you had typed it yourself, because in the only way that counts, you did.
Calibrate your judgment in public. You ask questions when you are unsure. You explain why you accepted or rejected something the model produced. You bring options to your tech lead instead of asking what to do. This is how you grow.
Read code before you write code. You understand the part of the system you are about to touch before you change it. You navigate the codebase fluently, and you use AI to accelerate exploration, not to skip it.
Take observability and testing seriously from day one. You don't ship a feature without thinking about how you'll know if it's working in production. You write the tests that matter, not the tests that pad the coverage report.
Participate in code review with curiosity. You review other engineers' PRs (including senior ones) and ask questions. Good engineering culture is built through code review, and we want yours from day one.
Understand what you are building and why. You learn the business behind the squad you are in. You can explain what your code does for our customers in plain language. If you can't, you push to learn until you can.
Be on-call for what you build. You participate in on-call rotation alongside your squad. Production teaches lessons that no book can.
Production experience as a software engineer, including ownership of features that real users depended on. We are open on years; we are not open on whether you have shipped real things.
Strong engineering fundamentals in a modern stack. Elixir/OTP is the home of our core platform and is what you will eventually work in, but for this role, strong production experience in any modern backend language (Elixir, Go, Rust, TypeScript/Node, Python, Ruby, Kotlin, Java) is acceptable, as long as you have the judgment and curiosity to ramp into Elixir quickly with senior support.
Solid PostgreSQL fundamentals. You understand schemas, indexes, basic query plans, and what a slow query looks like.
Working understanding of distributed systems concepts. You don't need years of war stories, but you should know what a message queue is for, why idempotency matters, and why "just retry it" is sometimes wrong.
B2B SaaS context awareness. You have shipped to environments where reliability matters, or you can credibly explain why you understand it does.
Comfort with observability and debugging in production. Logs, metrics, traces. You know that "it works on my machine" is the start of an investigation, not the end of one.
Daily use of AI tools in real engineering work. Active, judgment-driven use of AI tools in your current workflow, with the ability to walk us through a recent piece of work and explain how you used AI to produce it and where you intervened.
Fluent technical English. You read documentation, write specs, and participate in code review in English without friction.
Experience with Elixir/OTP in production. Not required, but it accelerates your ramp significantly.
Experience with React and TypeScript for the frontend portions of our stack.
Hands-on familiarity with AWS (EC2, RDS, S3, IAM) and container orchestration.
Experience designing and consuming REST or GraphQL APIs in real systems.
Familiarity with CI/CD pipelines and modern deployment practices (feature flags, staging environments).
Background in fleet management, telematics, logistics, fintech, or hardware-adjacent systems, or any domain with similar real-world consequences when the software misbehaves.
Contributions to open source, technical writing, side projects, or any artifact that lets us see how you think.
Our interview process is transparent and focused on judgment, not trivia. We allow and encourage the use of AI tools during technical stages, the same way you would use them at work. What we evaluate is how you plan, decide, review, and justify your choices, not how fast you can type. Whiteboard algorithm puzzles are not our thing.
Benefits of being INFLEET
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