Engineering Lead

Há 4 dias

Caxias do Sul, Brasil Genius Tempo inteiro

Engineering Lead (AI-Powered Digital Products)We're looking for an Engineering Lead who builds systems with clarity, speed, and leverage.
This role is central to how we operate.
You'll lead through architecture, code, and clean abstractions — not people management.
You'll work directly with product, design, and generalists to create the internal infrastructure that allows our small team to operate at 5-10x capacity.We're not shipping AI features to check a box.
We're building AI-native workflows — tools that shift how people think, work, and ship.
Every system you help build will start with internal use.
Once it consistently improves human output, we'll commercialize it.This role requires a builder who thinks long-term but ships in short loops.
Someone who sees product quality and infrastructure quality as two sides of the same problem.Salary: Highly competitive package aligned with your experience level, technical capability, and local market rates + an incentive program that includes high-performing hires.
($4,000 - $6,000)Location: RemoteSchedule: Fully remote position with flexible working hours defined as: minimum hours per week that can be worked flexibly throughout the day, depending on product lifecycle needs and priorities.ResponsibilitiesBuild backend systems and infrastructure from scratch — APIs, pipelines, orchestration, storageOwn full-stack workflows: light front-end (React, Next.js) to backend (Python, Node, etc.) to deploymentDesign and evaluate LLM-integrated workflows that assist or automate high-value tasksDefine system architecture and technical direction with an eye toward composability and maintainabilityCollaborate across product and design to scope, build, and iterate quickly, internal-first, user-facing secondEvaluate and integrate emerging AI capabilities (retrieval, agents, reasoning frameworks, etc.)Identify, adapt, and integrate open-source tools and frameworks where useful — always optimizing for speed, clarity, and leverageDebug, refactor, and improve systems as they grow — no handoffs, no silosQualificationsStrong experience building and scaling backend systems in production (Python, Node, Go, or similar)Familiarity with LLMs, prompt engineering, or workflow-based AI integrationsExperience in building and iterating on algorithms and their use with AI workflowsComfort working across the stack — you don't need to love front-end, but you're not blocked by itAbility to work autonomously and make smart decisions with imperfect informationFluency with cloud infra (AWS, GCP, etc.), CI/CD pipelines, containers, and deploymentSystems thinking: you design for long-term simplicity, not short-term hacksClear communication — concise, honest, directNice to haveExperience with agentic systems, vector databases, AI memory implementations, or task routing logicBackground in developer tools, internal platforms, or automation infrastructureComfort working in early-stage, zero-to-one product environmentsBenefitsEvery product we build is powered by the systems you help create.
If our infrastructure is tight, modular, and expressive — we move faster, ship better, and think more clearly as a team.This isn't a layer-above-the-team engineering role.
This is the team.
If you're looking for depth over headcount, clarity over consensus, and the chance to shape how AI systems get built from the inside out — we'd love to talk.
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