Build AI-powered product capabilities that automate, predict, and simplify user workflows Spendesk is looking for a Backend Software Engineer (IC3) to join our AI & Data Products squad and help build the next generation of product features powered by AI, ML, and intelligent automation. This is a hands‐on backend role focused on turning predictive models, LLM capabilities, and business intelligence into real product experiences. You will work on backend services, APIs and MCPs that bring automation, prediction, and assisted decision‐making into Spendesk's user journeys, helping reduce manual work and make our product more proactive and intelligent.

As a Backend Software Engineer (IC3) in the AI & Data Products squad, you will design, build, and operate backend services that power AI‐native and ML‐native product features. In practice, this means partnering with ML Engineers to productionize predictive logic, expose it through clean APIs and services, and integrate it into workflows that automate tasks, simplify decision‐making, or anticipate user needs. backend services that make AI capabilities reusable across multiple product flows This role requires both strong backend engineering and genuine interest in AI‐powered product design. TypeScript Node.js for backend and banking applications React on the frontend PostgreSQL for data storage; Redis, SQS, and Kafka for jobs, queues, and event streaming Terraform to define infrastructure as code Kubernetes, Lambdas, and Step Functions to run our applications AWS as our cloud provider, including AWS Bedrock for LLM access GitHub Actions for CI You do not need to be an ML engineer, but you must be comfortable integrating predictive or generative capabilities into backend systems and user‐facing product workflows.

Backend services for AI and ML‐powered product features Design, build, and operate backend services and APIs that power AI‐driven, ML‐driven, or automation‐heavy product capabilities. Translate predictive logic and AI outputs into reliable backend behaviors that can be consumed by user‐facing product flows. Ensure features are designed for production, not just experimentation,



with clear ownership of deployment, monitoring, and maintainability.

Integrate model‐serving APIs or LLM calls into robust backend services (your squad, or the applicative squad's services) with proper retries, fallbacks, and observability. Help define evaluation and monitoring patterns that make intelligent product behaviors measurable over time. Build backend capabilities that help automate repetitive tasks, anticipate user needs, or simplify complex workflows.

Work on product experiences where AI or ML can reduce manual effort, improve decision quality, or shorten time to value for users. Partner with Product and Design to turn ambiguous ideas into concrete backend implementations with measurable impact. Build with responsible data handling, security, and privacy by default, especially when features interact with sensitive financial workflows.

Embrace a "you build it, you run it" mindset, owning the health and quality of what you ship. Collaborate with applicative squads (or join them for a quarter) to integrate AI and ML services into existing user journeys and backend systems. Share best practices in backend reliability, production readiness, and AI feature delivery across the engineering organization.

Significant experience on backend software engineering experience in production environments. A strong track record of designing and shipping reliable backend services with measurable user or business impact. Technical & data skills Strong backend engineering skills with TypeScript / Node.js or adjacent technologies.

Familiarity with technologies such as Kafka, SQS, Step Functions, PostgreSQL, and modern observability practices. Highly autonomous and comfortable owning backend systems from design to production. Fluent in written and spoken English, our business language.





AI‐first, product‐led: prototype fast, dogfooding, iterate based on data You build it, you run it: owning deployment, monitoring, and continuous improvements PM, Design, ML Engineering, and Backend Engineering work together toward outcomes Pragmatic engineering: we optimize for impact, not theoretical perfection You've shipped or materially advanced a production‐grade backend service powering an AI‐driven or ML‐driven product capability. You've partnered effectively with one or more of the squad's ML Engineers to turn predictive or generative logic into a reliable user‐facing backend flow. You've improved the production readiness of an intelligent feature, for example through better observability, service integration, fallback handling, or evaluation metrics.

You've contributed to a reusable backend pattern that makes future AI‐powered product features easier to build across Spendesk. We're primarily hiring in Paris, London or Barcelona with a flexible hybrid setup. Outstanding remote candidates may be considered, but this is not a remote‐first role.

Spendesk is the AI‐powered spend management and procurement platform that transforms company spending. By simplifying procurement, payment cards, expense management, invoice processing, and accounting automation, Spendesk sets the new standard for spending at work. Its single, intelligent solution makes efficient spending easy for employees and gives finance leaders the full visibility and control they need across all company spend, even in multi‐entity structures.

Trusted by thousands of companies, Spendesk supports over 200,000 users across brands such as Payfit, Accor, Welcome to the Jungle, Swile, Big Mamma, Malt and Yousign. Versátil on‐site and remote policy Latest Apple equipment — the tools you need to excel Great office snacks — to fuel your day We also offer location‐specific benefits tailored to each market, including health insurance, wellness allowances, commuter support, meal vouchers, and gym memberships — ensuring you're well supported wherever you're based.

📌 Backend Software Engineer (Remoto) (Cataluña)
🏢 Spendesk
📍 Cataluña