Engineering Lead

1 semana atrás


Salvador, 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.#J-18808-Ljbffr


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