Productionization of ML and LLM Capabilities

You Will:

• Partner closely with the squad’s ML Engineers to productionize predictive models and LLM-driven capabilities.
• 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.
• Contribute to the engineering patterns that allow ML and AI capabilities to be reused across multiple product features.

Automation, Prediction & Workflow Simplification

You Will:

• 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.
• Bring pragmatism to delivery, balancing experimentation speed with long-term maintainability and trust.

Reliability, Observability & Operational Ownership

You Will:

• Instrument services with logs, tracing, and metrics to support production visibility and continuous improvement.
• Define and uphold standards around latency, resilience, failure handling, and cost efficiency for AI-powered services.
• 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.

Cross-functional Collaboration

You Will:

• Work hand-in-hand with ML Engineers, Product Managers, and Designers to deliver AI-powered product capabilities end-to-end.
• Collaborate with applicative squads (or join them for a quarter) to integrate AI and ML services into existing user journeys and backend systems.
• Help define the technical interfaces and integration patterns that make intelligent services easier to adopt across the product.
• Share best practices in backend reliability, production readiness, and AI feature delivery across the engineering organization.

What We’re Looking For

Experience & Background

You Have:

• 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.
• Experience contributing to complex product initiatives in fast-paced, cross-functional teams.
• Exposure to ML-enabled or AI-enabled product features is a strong plus.

You Have:

• Technical & data skills

  • Strong backend engineering skills with TypeScript / Node.js or adjacent technologies.
  • Experience designing APIs and service layers for complex product workflows.
  • Good understanding of distributed systems, async processing, and operational reliability.
  • Practical experience, or strong interest, in integrating predictive models, LLM APIs, or other AI capabilities into product backends.
  • Familiarity with technologies such as Kafka, SQS, Step Functions, PostgreSQL, and modern observability practices.

• Leadership & collaboration

  • Highly autonomous and comfortable owning backend systems from design to production.
  • Product-minded, customer-focused, and motivated by building features that create visible value for end users.
  • Comfortable working closely with ML Engineers and translating their outputs into durable product capabilities.
  • Pragmatic and impact-driven, able to move from experimentation to production without losing engineering rigor.
  • Fluent in written and spoken English, our business language.

Nice To Have:

• Experience productionizing ML-backed features such as classification, recommendation, forecasting, or automation
• Experience integrating LLM-backed capabilities into product workflows
• Familiarity with evaluation patterns for AI-powered features
• Experience in SaaS, fintech, or regulated environments

Not ticking every box? We’d still love to hear from you. At Spendesk, we value skills, potential, and diverse experiences. If this role excites you and you believe you could contribute, we encourage you to apply.

How We Work

• AI-first, product-led: prototype fast, dogfooding, iterate based on data
• You build it, you run it: owning deployment, monitoring, and continuous improvements
• Collaboration by default: PM, Design, ML Engineering, and Backend Engineering work together toward outcomes
• Pragmatic engineering: we optimize for impact, not theoretical perfection

What Success Looks Like In Your First 90 Days

• 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.

Location and Ways of Working

We value regular in-person collaboration. 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.

Hiring Process:

• HR screening call
• Discussion with the Hiring Manager
• Technical interview, live coding, and/or system design depending on profile
• Final interview with leadership

As we are an international team, please submit your application and CV in English.

About Spendesk

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. With offices in the United Kingdom, France, Spain, and Germany, Spendesk also puts community at the heart of its mission.

For more information: [www.spendesk.com/press](http://www.spendesk.com