Principal Backend Engineer

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🕒 April 16

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Jeeves

WebsiteLinkedInAll Job Openings

51 - 200 employees

💸 Finance

💳 Fintech

Finance • Fintech

Jeeves is a financial platform offering streamlined solutions for global finance management. It allows companies to issue cards, send payments, and manage expenses through an all-in-one platform available in over 25 countries globally. By integrating various financial services, Jeeves increases efficiency and saves costs for businesses traditionally burdened by disjointed financial systems. With offerings such as international fund transfers, competitive FX rates, expense management, and direct accounting integrations, Jeeves enhances operational capabilities across multiple currencies and regions. Although not a bank, it partners with licensed banks and financial institutions to provide these services.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

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