Remote job · el mes pasado
Construirás y operarás pipelines de datos en AWS, servicios Java/Spring Boot y funciones de IA como aplicaciones de IA generativa/RAG y ML predictivo para churn y recomendaciones en una plataforma de fidelización de clientes para restaurantes.
About Us: Incentivio is the intelligent guest engagement platform helping multi-unit restaurant brands turn guests into growth. Our unified platform brings online ordering, loyalty, marketing automation, and analytics into one system—powered by AI that personalizes engagement and helps predict churn. We help restaurants turn one-time visitors into loyal regulars while maintaining ownership of their data and brand. About the Position: We are seeking a Data & AI Engineer to build and operate data platforms and AI-powered applications on AWS. You will combine strong Java backend engineering, practical Python skills, and experience with AWS data and AI services to deliver reliable analytics, intelligent automation, and personalized guest experiences. Our existing environment includes Java and Spring Boot services, large-scale MySQL and MongoDB stores, integrations with partner POS and payment systems, and a Hive data lake on Amazon EMR. You will strengthen this foundation and help extend it using AWS services for data processing, predictive analytics, and generative AI. This is a hands-on engineering role with ownership across data ingestion, modeling, application development, AI integration, deployment, and production operations. Potential AI use cases include guest segmentation, churn prediction, personalized recommendations, automated business insights, and natural-language access to restaurant performance data. Responsibilities: • Design and build scalable AWS-based data, backend, and AI solutions with a focus on reliability, security, performance, and cost. • Develop Java/Spring Boot services, APIs, data models, and integrations across MySQL, MongoDB, and third-party platforms. • Build and maintain reliable data ingestion and processing pipelines for transaction, guest, ordering, loyalty, and payment data. • Develop and modernize the AWS data platform using services including S3, EMR, Spark, Glue, and Athena. • Create trusted, reusable datasets and data models for analytics, customer intelligence, and AI/ML applications. • Build generative AI and RAG applications using Amazon Bedrock, OpenSearch, and related technologies. • Support predictive ML use cases including churn, recommendations, and segmentation. • Establish testing, monitoring, and evaluation for data pipelines, AI quality, application performance, and production reliability. • Ensure strong security, privacy, tenant isolation, and governance of customer and guest data. • Maintain engineering quality through CI/CD, infrastructure as code, automated testing, code reviews, and documentation. Requirements: • 5+ years of production software or data engineering experience, with strong Java/Spring Boot and AWS experience. • Strong Java, SQL, data modeling, and database optimization skills, including MySQL and MongoDB. • Proficiency in Python for data processing, AI workflows, and automation. • Hands-on AWS data engineering experience with S3 and distributed processing technologies such as EMR, Glue, or Spark. • Experience building AI/ML applications using technologies such as Amazon Bedrock and SageMaker, including generative AI, RAG, embeddings, and model evaluation. • Experience designing reliable data pipelines, including incremental processing, schema evolution, reconciliation, and failure recovery. • Strong understanding of AWS infrastructure, messaging, security, monitoring, and containerized applications. • Experience with automated testing, CI/CD, infrastructure as code, and production monitoring. • Strong engineering judgment, communication, troubleshooting skills, and effective use of AI-assisted development tools. Nice to have: Experience with OpenSearch, streaming/CDC technologies, advanced data lake architectures, predictive ML/recommendation systems, and restaurant technology, payments, loyalty, or POS integrations.
Publicada el 24 sept 2026
