Buscar empleo: 232 ofertas de trabajo de apple en Barcelona (julio 2026)

Backend Software Engineer (AI Squad)

hace 6 horas

Barcelona

ph3Build AI‑powered product capabilities that automate, predict, and simplify user workflows /h3 pSpendesk 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. /p pThis hands‑on backend role focuses on turning predictive models, LLM capabilities, and business intelligence into real product experiences. You will build backend services, APIs and MCPs that bring automation, prediction, and assisted decision‑making into Spendesk’s user journeys, reducing manual work and making our product more proactive and intelligent. /p pYou will collaborate closely with the 3 ML Engineers, Product Managers, Designers and other squads across Spendesk to build production‑grade services that expose ML‑driven and LLM‑driven capabilities in ways that are reliable, observable, and valuable for end users. /p h3About The Role /h3 pAs 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. /p pYour mission is to help Spendesk move from isolated intelligence components to real, user‑facing product capabilities. In practice, you’ll partner with ML Engineers to production‑ize predictive logic, expose it through clean APIs and services, and integrate it into workflows that automate tasks, simplify decision‑making, or anticipate user needs. /p h3Features You May Work On /h3 ul liAutomated categorization and enrichment of spend‑related workflows /li liPredictive assistance in finance or accounting journeys /li liIntelligent recommendations based on historical behaviour or contextual signals /li liLLM‑powered experiences that simplify user actions and reduce friction /li liBackend services that make AI capabilities reusable across multiple product flows /li /ul h3Key Responsibilities /h3 h3Backend services for AI and ML‑powered product features /h3 ul liDesign, build, and operate backend services and APIs that power AI‑driven, ML‑driven, or automation‑heavy product capabilities. /li liTranslate predictive logic and AI outputs into reliable backend behaviours that can be consumed by user‑facing product flows. /li liBuild the service layer that allows intelligent features to be integrated into real workflows with strong standards on latency, reliability, and security. /li liEnsure features are designed for production, not just experimentation, with clear ownership of deployment, monitoring, and maintainability. /li /ul h3Productionisation of ML and LLM capabilities /h3 ul liPartner closely with the squad’s ML Engineers to production‑ize predictive models and LLM‑driven capabilities. /li liIntegrate model‑serving APIs or LLM calls into robust backend services with proper retries, fallbacks, and observability. /li liHelp define evaluation and monitoring patterns that make intelligent product behaviours measurable over time. /li liContribute to engineering patterns that allow ML and AI capabilities to be reused across multiple product features. /li /ul h3Automation, prediction workflow simplification /h3 ul liBuild backend capabilities that help automate repetitive tasks, anticipate user needs, or simplify complex workflows. /li liWork on product experiences where AI or ML can reduce manual effort, improve decision quality, or shorten time to value for users. /li liPartner with Product and Design to turn ambiguous ideas into concrete backend implementations with measurable impact. /li liBring pragmatism to delivery, balancing experimentation speed with long‑term maintainability and trust. /li /ul h3Reliability, observability operational ownership /h3 ul liInstrument services with logs, tracing, and metrics to support production visibility and continuous improvement. /li liDefine and uphold standards around latency, resilience, failure handling, and cost efficiency for AI‑powered services. /li liBuild with responsible data handling, security, and privacy by default, especially when features interact with sensitive financial workflows. /li liEmbrace a “you build it, you run it” mindset, owning the health and quality of what you ship. /li /ul h3Cross‑functional collaboration /h3 ul liWork hand‑in‑hand with ML Engineers, Product Managers, and Designers to deliver AI‑powered product capabilities end‑to‑end. /li liCollaborate with applicative squads (or join them for a quarter) to integrate AI and ML services into existing user journeys and backend systems. /li liHelp define the technical interfaces and integration patterns that make intelligent services easier to adopt across the product. /li liShare best practices in backend reliability, production readiness, and AI feature delivery across the engineering organization. /li /ul h3What we’re looking for /h3 h3Experience background /h3 ul liSignificant experience in backend software engineering in production environments. /li liA strong track record of designing and shipping reliable backend services with measurable user or business impact. /li liExperience contributing to complex product initiatives in fast‑paced, cross‑functional teams. /li liExposure to ML‑enabled or AI‑enabled product features is a strong plus. /li /ul h3Technical data skills /h3 ul liStrong backend engineering skills with TypeScript / Node.js or adjacent technologies. /li liExperience designing APIs and service layers for complex product workflows. /li liGood understanding of distributed systems, async processing, and operational reliability. /li liPractical experience or strong interest in integrating predictive models, LLM APIs, or other AI capabilities into product backends. /li liFamiliarity with technologies such as Kafka, SQS, Step Functions, PostgreSQL, and modern observability practices. /li /ul h3Leadership collaboration /h3 ul liHighly autonomous and comfortable owning backend systems from design to production. /li liProduct‑minded, customer‑focused, and motivated by building features that create visible value for end users. /li liComfortable working closely with ML Engineers and translating their outputs into durable product capabilities. /li liPragmatic and impact‑driven, able to move from experimentation to production without losing engineering rigor. /li liFluent in written and spoken English, our business language. /li /ul h3Nice To Have /h3 ul liExperience productionising ML‑backed features such as classification, recommendation, forecasting, or automation. /li liExperience integrating LLM‑backed capabilities into product workflows. /li liFamiliarity with evaluation patterns for AI‑powered features. /li liExperience in SaaS, fintech, or regulated environments. /li /ul h3Location and ways of working /h3 ul liWe 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. /li /ul h3What success looks like in your first 90 days /h3 ul liYou’ve shipped or materially advanced a production‑grade backend service powering an AI‑driven or ML‑driven product capability. /li liYou’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. /li liYou’ve improved the production readiness of an intelligent feature, e.g. through better observability, service integration, fallback handling, or evaluation metrics. /li liYou’ve contributed to a reusable backend pattern that makes future AI‑powered product features easier to build across Spendesk. /li /ul h3Benefits /h3 ul liFlexible on‑site and remote policy /li liLatest Apple equipment — the tools you need to excel /li liAccess to Moka.care — for emotional and mental health wellbeing /li liGreat office snacks — to fuel your day /li liA positive team to work with daily! /li liLocation‑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. /li /ul h3Diversity Inclusion /h3 pAt Spendesk, we’re committed to fostering an environment where all differences are encouraged, supported and celebrated. We’re building our culture for everyone, with everyone. Our goal is to attract and build a diverse, equal and inclusive team, where everyone feels welcome and we truly embrace and encourage people from all backgrounds to apply. /p /p #J-18808-Ljbffr

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