Principal Backend Engineer

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Jeeves

SiteLinkedInTodas as Vagas

51 - 200 funcionários

💼 Consultoria

📦 Logística

📣 Marketing

Consulting • Logistics • Marketing

Jeeves é uma plataforma financeira que oferece soluções simplificadas para a gestão de finanças globais. Ela permite que as empresas emitam cartões, enviem pagamentos e gerenciem despesas em uma plataforma tudo em um, disponível em mais de 25 países ao redor do mundo. Ao integrar diversos serviços financeiros, a Jeeves aumenta a eficiência e reduz custos para empresas tradicionalmente sobrecarregadas por sistemas financeiros fragmentados. Com ofertas como transferências internacionais de fundos, taxas de câmbio (FX) competitivas, gestão de despesas e integrações diretas com a contabilidade, a Jeeves amplia as capacidades operacionais em múltiplas moedas e regiões. Embora não seja um banco, a empresa faz parcerias com bancos e instituições financeiras licenciadas para oferecer esses serviços.

Descrição

• Design, build, and maintain scalable, reliable backend services that process financial transactions and serve Jeeves customers across 20+ countries. • Write clean, testable, production-quality code in Go, Python, or Node.js/TypeScript; participate actively in design and code reviews. • Build and consume RESTful and GraphQL APIs; design inter-service communication using gRPC, message queues, and event-driven architectures. • Design and optimize relational and non-relational database schemas (PostgreSQL, MongoDB, Redis) for correctness, performance, and scale. • Own backend features end-to-end — from scoping and technical design through deployment, monitoring, and iteration. • Implement security best practices: authentication, authorization, input validation, and data protection across distributed services. • Integrate LLM API calls (e.g., OpenAI, Anthropic) into backend services as product features — such as spend categorization, document parsing, or natural language workflows — ensuring those integrations are reliable, observable, and cost-efficient. • Build backend pipelines that consume AI-generated outputs safely: validate structured outputs, handle fallback scenarios, and design graceful degradation when AI services are unavailable or return low-confidence results. • Collaborate with AI and data science teams to integrate model outputs into backend APIs — bridging experimental AI work and production systems. • Use AI coding tools (GitHub Copilot, Claude, Cursor, etc.) fluently as part of your everyday development workflow. • Instrument services with structured logging, distributed tracing, and metrics for full operational visibility. • Participate in on-call rotation; respond to production incidents and contribute to post-incident reviews. • Contribute to CI/CD pipeline improvements, testing infrastructure, and deployment practices. • Work closely with engineering, product, compliance, and data teams across multiple time zones and regions — communicating in both English and Spanish or Portuguese as the situation requires. • Contribute to a globally distributed engineering culture through thorough documentation, async design reviews, and thoughtful pull request feedback. • Bring your regional perspective to product and engineering conversations — our LATAM customers have specific needs, and engineers who understand those markets make our product better.

🎯 Requisitos

• 5+ years of professional backend engineering experience building and operating production systems. • Fluent in English — professional fluency required for daily work with global teams in written and spoken contexts. • Fluent in Spanish or Portuguese — required for collaboration with LATAM teammates, customers, and operational partners. • Strong proficiency in at least one backend language: Go, Python, or Node.js/TypeScript. • Experience designing and building RESTful APIs, microservices, and event-driven backend systems. • Solid understanding of relational databases (PostgreSQL preferred): schema design, query optimization, and data modeling. • Experience with cloud infrastructure (AWS, GCP, or Azure), containerization (Docker, Kubernetes), and CI/CD pipelines. • Demonstrated ability to integrate third-party APIs reliably in production — including error handling, retry logic, and observability. • Experience working on globally distributed teams across time zones and regions. • Comfortable using AI tools as part of everyday engineering work — integrating LLM API outputs into backend services and using AI coding assistants fluently.

🏖️ Benefícios

• Health insurance • Retirement plans • Paid time off • Flexible work arrangements • Professional development • Remote work options