Backend Python Developer (Full-Time Remote)

Senior Backend Engineer - Python & AI Si cree que es el candidato ideal para la siguiente oportunidad, envíe su solicitud después de leer la descripción completa.We are looking for a Senior Backend Engineer to join an AI Engineering team within a large international technology environment.In this role, you will design, build, and operate robust Python backend services that power AI-enabled applications and reusable engineering capabilities across a complex enterprise ecosystem.This is a highly hands-on senior individual contributor position, focused on solving real production challenges, making sound architectural decisions, and turning AI and data-science capabilities into secure, reliable, scalable, and maintainable software.You will take ownership of backend services from initial design through production operation, working closely with Data Scientists, Product Managers, Platform Engineers, Security Specialists, and Architects.If you enjoy building production-grade Python services, designing APIs and distributed systems, working with AWS, and integrating AI/LLM capabilities into real-world applications, this could be a great fit.Design, build, and maintain scalable backend services and APIs using Python Own backend services end-to-end, from architecture and implementation through deployment and production operation Integrate AI models, Large Language Models (LLMs), and Machine Learning services into production systems Define service boundaries, data models, persistence strategies, and integration contracts Work with relational databases, data modelling, schema evolution, and persistence strategies Deploy and operate backend services in AWS cloud environments Design services with reliability, security, observability, performance, and cost in mind Handle production AI concerns such as latency, structured outputs, sensitive data, model failures, and external API limitations Improve automated testing, CI/CD pipelines, monitoring, dashboards, logging, and alerting Work with Docker and Kubernetes to containerise and operate backend workloads Participate in code reviews and help establish strong backend engineering standards Mentor other engineers and share software engineering best practices Collaborate closely with Data Scientists, Product Managers, Platform Engineers, Security Specialists, and Architects Typically 7+ years of experience in Backend Software Engineering, although technical depth, ownership, and impact are more important than an exact number of years Strong Python software engineering skills Solid experience designing and building backend services and REST APIs Strong understanding of software architecture, service boundaries, distributed systems, and failure handling Experience with relational databases, data modelling, and schema evolution Hands-on experience deploying and operating production services in cloud environments, ideally AWS Strong knowledge of software testing and engineering best practices Experience with CI/CD pipelines and production deployment processes Solid understanding of observability, logging, monitoring, dashboards, and alerting Experience with Docker and Kubernetes Practical understanding of security, privacy, sensitive data, and data protection principles Experience working effectively across engineering, product, data, platform, and architecture teams Fluent English and Spanish Experience with FastAPI Hands-on experience with AWS services and cloud-native architectures Experience with Amazon EKS Familiarity with Infrastructure as Code, especially Terraform Experience with PostgreSQL, Amazon Aurora, or similar relational databases Experience integrating AI, Machine Learning, or LLM capabilities into production backend systems Experience in complex enterprise or large-scale digital environments Hybrid model - 2 days onsite per week in Viladecans, Barcelona Why join this project?Build production-grade backend systems that power real AI-enabled applications Work deeply with Python, APIs, distributed systems, databases, and cloud-native technologies Gain exposure to real-world AI and LLM integration without moving away from hands-on software engineering Work in an AWS-based environment with modern cloud and platform engineering practices Influence architecture, engineering standards, reliability, observability, and production quality ** per year training budget and continuous learning opportunities.Private health insurance and benefits package.Flexible working hours and hybrid model.Team buildings, global events, and strong tech communities.Information Security Notice The employee will have access to confidential information related to Capitole and the assigned project.

This is a highly hands-on senior individual contributor position, focused on solving real production challenges, making sound architectural decisions, and turning AI and data-science capabilities into secure, reliable, scalable, and maintainable software. You will take ownership of backend services from initial design through production operation, working closely with Data Scientists, Product Managers, Platform Engineers, Security Specialists, and Architects. If you enjoy building production-grade Python services, designing APIs and distributed systems, working with AWS, and integrating AI/LLM capabilities into real-world applications, this could be a great fit. Design, build, and maintain scalable backend services and APIs using Python Own backend services end-to-end, from architecture and implementation through deployment and production operation Integrate AI models, Large Language Models (LLMs), and Machine Learning services into production systems Define service boundaries, data models, persistence strategies, and integration contracts Work with relational databases, data modelling, schema evolution, and persistence strategies Deploy and operate backend services in AWS cloud environments Design services with reliability, security, observability, performance, and cost in mind Handle production AI concerns such as latency, structured outputs, sensitive data, model failures, and external API limitations Improve automated testing, CI/CD pipelines, monitoring, dashboards, logging, and alerting Work with Docker and Kubernetes to containerise and operate backend workloads Participate in code reviews and help establish strong backend engineering standards Mentor other engineers and share software engineering best practices Collaborate closely with Data Scientists, Product Managers, Platform Engineers, Security Specialists, and Architects Typically 7+ years of experience in Backend Software Engineering, although technical depth, ownership, and impact are more important than an exact number of years Strong Python software engineering skills Solid experience designing and building backend services and REST APIs Strong understanding of software architecture, service boundaries, distributed systems, and failure handling Experience with relational databases, data modelling, and schema evolution Hands-on experience deploying and operating production services in cloud environments, ideally AWS Strong knowledge of software testing and engineering best practices Experience with CI/CD pipelines and production deployment processes Solid understanding of observability, logging, monitoring, dashboards, and alerting Experience with Docker and Kubernetes Practical understanding of security, privacy, sensitive data, and data protection principles Experience working effectively across engineering, product, data, platform, and architecture teams Fluent English and Spanish Experience with FastAPI Hands-on experience with AWS services and cloud-native architectures Experience with Amazon EKS Familiarity with Infrastructure as Code, especially Terraform Experience with PostgreSQL, Amazon Aurora, or similar relational databases Experience integrating AI, Machine Learning, or LLM capabilities into production backend systems Experience in complex enterprise or large-scale digital environments Hybrid model - 2 days onsite per week in Viladecans, Barcelona Why join this project?

Build production-grade backend systems that power real AI-enabled applications Work deeply with Python, APIs, distributed systems, databases, and cloud-native technologies Gain exposure to real-world AI and LLM integration without moving away from hands-on software engineering Work in an AWS-based environment with modern cloud and platform engineering practices Influence architecture, engineering standards, reliability, observability, and production quality ** per year training budget and continuous learning opportunities. Private health insurance and benefits package. Flexible working hours and hybrid model. Team buildings, global events, and strong tech communities. Information Security Notice The employee will have access to confidential information related to Capitole and the assigned project.