Senior Backend Engineer

Jeeves

2d•Remote

About The Position

Jeeves is hiring a Senior Backend Engineer to design and build backend systems for its stablecoin-native financial platform, including payments, cards, spend management, and compliance infrastructure serving businesses across the Americas and beyond. This is a backend engineering role for someone who can use AI tools effectively, identify where AI can improve development and product capabilities, and integrate AI-powered features into production systems. The role involves building scalable services and APIs, working with databases and distributed architectures, and owning backend features from technical design through deployment and ongoing improvement. It also includes integrating LLM-powered features, ensuring AI-generated outputs are handled safely, and collaborating with AI and data science teams to bring model outputs into production systems. The engineer will contribute to service reliability and operations, including observability, on-call response, incident reviews, CI/CD, testing, and deployment practices. They will collaborate with engineering, product, compliance, and data teams across regions and time zones, communicating in English and Spanish or Portuguese as circumstances require. The position is full-time and remote.

Requirements

At least 5 years of professional backend engineering experience building and operating production systems.
Professional fluency in written and spoken English for daily work with global teams.
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, preferably PostgreSQL, including schema design, query optimization, and data modeling.
Experience with cloud infrastructure such as AWS, GCP, or Azure; containerization using Docker and 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.
Comfort using AI tools in everyday engineering work, integrating LLM API outputs into backend services, and using AI coding assistants fluently.

Nice To Haves

Experience in fintech, financial services, payments, or a regulated industry; familiarity with ledger systems, payment rails, or financial compliance such as KYC/AML or PCI-DSS.
Fluency in Spanish or Portuguese for collaboration with LATAM teammates, customers, and operational partners.
Prior experience at a startup or high-growth scale-up and comfort building amid ambiguity without heavy process support.
Experience with multi-currency systems or cross-border payment processing.
Familiarity with message queue systems such as Kafka or RabbitMQ and event-driven architecture.
Global work experience at companies operating across multiple countries and regulatory environments.

Responsibilities

Design, build, and maintain scalable, reliable backend services that process financial transactions and serve customers across more than 20 countries.
Write clean, testable, production-quality code in Go, Python, or Node.js/TypeScript, and participate 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, including PostgreSQL, MongoDB, and Redis.
Own backend features from scoping and technical design through deployment, monitoring, and iteration.
Implement security best practices, including authentication, authorization, input validation, and data protection across distributed services.
Integrate LLM API calls into backend services as product features, ensuring integrations are reliable, observable, and cost-efficient.
Build backend pipelines that safely consume AI-generated outputs by validating structured outputs, handling fallbacks, and supporting graceful degradation.
Collaborate with AI and data science teams to integrate model outputs into backend APIs and production systems.
Use AI coding tools such as GitHub Copilot, Claude, and Cursor in everyday development.
Instrument services with structured logging, distributed tracing, and metrics.
Participate in the 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 with engineering, product, compliance, and data teams across time zones and regions, communicating in English and Spanish or Portuguese as needed.
Contribute to a distributed engineering culture through documentation, asynchronous design reviews, and thoughtful pull request feedback.
Bring regional perspective to product and engineering discussions, particularly regarding LATAM customer needs.