Software Engineer | Elixir
Infleet · BR ·
- Work mode
- Remote
- Category
- Software engineering
Infleet · BR ·
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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 already operate the way we believe engineering should be done in 2026: as orchestrators of AI, with sharp judgment, deep ownership, and obsession for the things that actually matter long term, namely maintainability, scale, observability, API design, testability, performance, and understanding of the business behind the code.
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 own critical parts of our platform end to end. You set the technical direction in your domain, decide what good looks like, and raise the bar for the engineers around you, while shipping production-grade software at the pace the business needs.
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 be accountable for the long-term health of the systems in that domain: how they evolve, how they fail, how they recover, how they scale, and how they integrate with the rest of the platform.
You will be expected to think in terms of systems, not tickets. You will write RFCs when the problem deserves one, you will design APIs that other squads can build against without surprises, you will be on-call for what you ship, and you will mentor less senior engineers in how to use AI responsibly to produce code that survives five years and not five sprints.
Fully remote, with 4 on-site gatherings per year in São Paulo.
Own a domain end to end. You are the technical reference for a part of the platform. You know how it works, how it fails, how it is observed, and how it should evolve. You make the call on architecture decisions inside that domain and write them down so others can review and challenge.
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.
Raise the engineering bar around you. You review PRs with depth, you push back when something is "fine" but not "good", and you teach the engineers around you, especially on how to combine AI productivity with engineering rigor.
Design APIs and contracts other teams build on. Internal APIs, public APIs, message schemas, event contracts: you treat them as products with users, versioning strategies, and backwards-compatibility budgets.
Build for observability from day one. Logs, metrics, traces, dashboards, alerts. You do not consider a feature done when it merges. You consider it done when you can answer "is it working in production right now?" in less than thirty seconds.
Own incidents in your domain. You participate in on-call rotation for the systems you build. You write postmortems that change behavior, not postmortems that satisfy a template.
Translate business into systems. You understand what a fleet manager is trying to do, why our customers pay us, and how the system you maintain contributes to that outcome. You can have the conversation in product review without needing a translator.
Make boring decisions intentionally. You choose the simpler database, the existing service, the well-understood pattern, when it is the right call. You also choose the new approach when the evidence supports it. Either way, you can articulate the trade-off.
Significant experience shipping production software, including time as a senior contributor on systems that real users depend on.
Elixir/OTP in production is required for this role. Production experience with Elixir/OTP is required for this role. As our core platform runs on Elixir, the scope of work demands deep codebase familiarity without a learning curve. We are non-negotiable on this requirement.
PostgreSQL at scale. You understand indexes, query plans, partitioning, connection pools, and what happens to your database when traffic grows 10x.
Distributed systems at production scale. Messaging (RabbitMQ, Kafka, Kinesis), event streaming, concurrency, retries, idempotency, eventual consistency. You have made the mistakes and learned from them.
B2B SaaS with real SLAs. You have lived through the difference between a hobby project and a system where downtime has a phone call attached to it.
Observability and on-call experience. You have debugged production systems under pressure. You have built dashboards that helped, and you have built dashboards that didn't, and you know the difference.
Daily use of AI tools in real engineering work. Not "tried Copilot once". Active, judgment-driven orchestration of AI tools in your current workflow, with strong opinions about what works, what doesn't, and where the model lies. You should be able to walk us through a recent piece of non-trivial 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 React and TypeScript for the frontend portions of our stack.
Hands-on familiarity with AWS (EC2, RDS, Kinesis, S3, IAM) and Kubernetes (EKS).
Experience designing and operating GraphQL APIs at scale.
Experience with CI/CD pipelines (GitHub Actions or similar) and pragmatic deployment practices (feature flags, canaries, blue/green).
Background in fleet management, telematics, logistics, fintech, or hardware-adjacent systems, or any domain with similar real-world consequences when the software misbehaves.
Experience operating Livebook, ETS/Mnesia, or other Erlang ecosystem tools in production.
Contributions to open source, technical writing, conference talks, or any other 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
stord · Remote - TX