Описание:Wizeline is a integral AI-native technology solutions provider that develops AI-powered digital products and platforms. It partners with clients to leverage data and AI, accelerate market entry, and drive business transformation.Задачи:Design, develop, and enhance scalable content and translation platforms using Java, Spring Boot, REST APIs, and microservices architecturesBuild and integrate LLM- and AI-powered translation capabilities into enterprise content-processing workflowsDevelop reliable APIs and backend services for translation requests, processing, and results, ensuring scalability, performance, and maintainabilityIntegrate with AI/LLM and machine-translation providers, evaluating opportunities to improve translation quality, scalability, cost, and latencyDesign and implement event-driven architectures using technologies such as Apache Kafka to support high-volume content-processing pipelinesIntegrate translation and content services with existing enterprise platforms, APIs, and downstream systemsDevelop solutions for multilingual content processing, supporting multiple languages, content types, and international publishing requirementsImplement error handling, retries, monitoring, logging, alerting, and other operational capabilities for reliable production systemsDevelop automated tests and validation mechanisms for translation workflow and service quality and reliabilityImprove performance and scalability as content and translation volumes increaseSupport production deployments, troubleshooting, incident resolution, and ongoing operational improvementsCollaborate with engineering, product, and client stakeholders to define technical solutions, participate in design discussions,



and translate business requirements into scalable softwareContribute to technical documentation, code reviews, CI/CD practices, and engineering standardsHelp evolve the platform architecture to support international expansion, additional languages, and new content typesStay current with developments in GenAI, LLMs, machine translation, multilingual NLP, cloud technologies and distributed systems, applying relevant practices to production solutionsТребования:Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field, or equivalent practical experienceAt least 4 years of professional software engineering experience, including strong experience developing enterprise applications with Java and Spring BootStrong experience designing and developing REST APIs and microservicesHands-on experience with cloud-based application development, preferably on Google Cloud Platform (GCP)Practical experience with Apache Kafka or similar event-driven messaging technologiesExperience developing or integrating LLM/AI-powered applications and APIs in production or enterprise environmentsExperience with machine translation, multilingual content processing, NLP, or related AI-driven content technologiesStrong understanding of software engineering practices, including Git, CI/CD, automated testing,



code reviews, and Agile methodologiesExperience integrating applications with existing enterprise platforms, APIs, and third-party servicesAbility to troubleshoot production issues and contribute to monitoring, logging, performance optimization, and operational supportStrong written and verbal English communication skillsБудет плюсом: experience with content-management, publishing, media, or digital content platforms; experience with LLM providers, AI APIs, or machine-translation platforms such as Google Cloud Translation, Azure AI Translator, AWS Translate, or equivalent services; familiarity with Google Cloud Platform services such as GKE, Cloud Run, Pub/Sub, Cloud Storage, BigQuery, or similar; experience with multilingual NLP, translation quality evaluation, language detection, or localization workflows; familiarity with AI/LLM orchestration frameworks and tools such as LangChain, LangGraph, LangSmith, or equivalent; experience implementing observability solutions using tools such as Cloud Monitoring, Cloud Logging, Datadog, Grafana, or equivalent; experience with Docker and containerized application deployments; experience with high-volume, distributed, or latency-sensitive systems; familiarity with media or publishing workflows, content pipelines, editorial systems, or international content distribution; comfort using AI tools to optimize day-to-day work, including development, analysis, research, testing, and automation, with the ability to identify opportunities to improve engineering workflowsУсловия:Specific benefits are determined by employment type and location
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📌 ai engineer for multilingual translation platforms (Barcelona)
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📍 Barcelona