📍 Job Overview

Job Title: Site Reliability Engineer - AI Platform
Company: N26
Location: Berlin, Germany
Job Type: Full-Time
Category: DevOps & Infrastructure
Date Posted: August 1, 2025
Experience Level: Mid-Level (2-5 years)
Remote Status: Remote OK

🚀 Role Summary

Key Responsibilities: Design, develop, and maintain reliable AI platform components, enabling machine learning and generative AI use cases. Ensure service reliability through deployment, monitoring, and incident response.
Key Skills: Infrastructure and reliability engineering, deployment automation, cloud-native development, AWS, Python, Go, TypeScript, Kubernetes, CI/CD, Terraform, Docker, networking, security, and compliance.

📝 Enhancement Note: This role requires a strong background in infrastructure and reliability engineering, with a focus on cloud-native development and AWS services. Familiarity with AI/ML-related services like SageMaker and Bedrock would be beneficial.

💻 Primary Responsibilities

Platform Component Development: Contribute to the design and development of platform components that enable machine learning and generative AI use cases across the company.
Service Reliability: Take ownership of reliable deployment, maintenance, monitoring, and incident response for our services.
Code Quality: Write high-quality, maintainable code and ensure our platform solutions are well-documented and testable.
Infrastructure Evolution: Work alongside senior engineers to evolve our infrastructure and build secure, compliant, and scalable solutions across cloud, networking, observability, and CI/CD domains.
Collaboration: Collaborate with ML Engineers, SREs, and other Platform teams to ensure operability and maintainability of AI capabilities offered across the company. Participate in code reviews, RFCs, documentation, and product discovery.
Proactive Problem-Solving: Identify technical or knowledge gaps and proactively work to address them, either independently or with the team.
Improving Engineering Practices: Help improve our engineering practices and team ways of working.

🎓 Skills & Qualifications

Education: Bachelor's degree in Computer Science, Engineering, or a related field. Relevant experience may be considered in lieu of a degree.

Experience: Proven experience (2-5 years) specifically in infrastructure and reliability engineering, including deployment automation, monitoring, incident management, and performance tuning.

Required Skills:

Proven experience in infrastructure and reliability engineering.
Solid programming skills in Python, Go, or TypeScript.
Familiarity with cloud-native development and AWS infrastructure, including some experience with services like SageMaker, Bedrock, or other AI/ML-related services.
Experience with Kubernetes, CI/CD pipelines (e.g., ArgoCD, GitHub Actions), Infrastructure-as-Code tools (e.g., Terraform), and containerization (Docker).
Working knowledge of networking, security, and compliance best practices in production environments.
Appreciation for good documentation, testing, and observability.

Preferred Skills:

Exposure to MLOps practices or working with Data Science/Machine Learning teams.
Familiarity with prompt-based or LLM-driven GenAI workflows.
Interest or prior experience in building developer-facing platforms and reusable abstractions.

📊 Web Portfolio & Project Requirements

Portfolio Essentials:

Demonstrate your experience in infrastructure and reliability engineering with relevant projects showcasing deployment automation, monitoring, and incident response.
Highlight your programming skills with code samples or projects showcasing your proficiency in Python, Go, or TypeScript.
Showcase your experience with cloud-native development, AWS infrastructure, and AI/ML-related services with relevant project examples.
Include examples of your work with Kubernetes, CI/CD pipelines, Infrastructure-as-Code tools, and containerization.

Technical Documentation:

Provide clear and concise documentation for your projects, explaining the architecture, deployment process, and any relevant technical details.
Include any relevant testing methodologies, performance metrics, and optimization techniques used in your projects.

📝 Enhancement Note: Given the role's focus on infrastructure and reliability engineering, your portfolio should emphasize your ability to design, develop, and maintain scalable, secure, and compliant solutions. Highlight your experience with deployment automation, monitoring, and incident response, as well as your proficiency in relevant programming languages and tools.

💵 Compensation & Benefits

Salary Range: €60,000 - €80,000 per year (based on experience and market research)

Benefits:

Competitive personal development budget
Work-from-home budget
Discounts on fitness and wellness memberships, language apps, and public transportation
Premium subscription on your personal N26 bank account, as well as subscriptions for friends and family members
Additional day of annual leave for each year of service
Relocation package with visa support (if applicable)

Working Hours: Full-time (40 hours per week)

🎯 Team & Company Context

Company Culture:

Industry: Fintech (Financial Technology)
Company Size: Medium (1,500+ employees)
Founded: 2013
Team Structure: The AI Platform team is part of the Platform Engineering domain, working collaboratively with product teams, other platform teams, and the company to build and maintain reliable, scalable, and secure infrastructure solutions for machine learning and generative AI capabilities.
Development Methodology: Agile/Scrum methodologies, code reviews, RFCs, and product discovery processes are used to ensure efficient collaboration and decision-making.

Company Website: https://n26.com/

📝 Enhancement Note: N26 is a well-established fintech company with a strong focus on digital banking and innovation. The AI Platform team plays a crucial role in enabling machine learning and generative AI use cases across the company, working closely with various teams to ensure operability and maintainability of AI capabilities.

📈 Career & Growth Analysis

Web Technology Career Level: Mid-Level Site Reliability Engineer (SRE) focusing on AI platform infrastructure and reliability.

Reporting Structure: This role reports directly to the Engineering Manager of the AI Platform team within the Platform Engineering domain.

Technical Impact: As an SRE in the AI Platform team, you will have a significant impact on the reliability, scalability, and security of AI platform components, enabling machine learning and generative AI use cases across the company.

Growth Opportunities:

Technical Growth: Develop your expertise in AI infrastructure, working alongside experienced engineers in Machine Learning, Backend, and Platform Engineering.
Leadership Potential: As the team and company grow, there may be opportunities to take on more senior roles or technical leadership positions within the AI Platform team or broader Platform Engineering domain.
Cross-Functional Collaboration: Work closely with ML Engineers, SREs, and other Platform teams to gain exposure to various aspects of AI platform development and maintenance.

📝 Enhancement Note: This role offers excellent opportunities for career growth and development within the AI infrastructure space. By joining the AI Platform team, you will have the chance to contribute meaningfully to the evolution of the AI platform that's at the heart of the company's highest value bets, helping to build a foundation for reliable, scalable, and democratized access to Machine Learning and GenAI capabilities across N26.

🌐 Work Environment

Office Type: Modern, collaborative workspace with a focus on digital banking and innovation.

Office Location(s): Berlin, Germany (with remote work options available)

Workspace Context:

Collaboration: Work in a cross-functional environment with a focus on practical impact, supporting product teams, the company, and customers.
Development Tools: Access to modern development tools, multiple monitors, and testing devices to ensure efficient and effective work.
Team Interaction: Collaborate with a diverse team of professionals, including ML Engineers, SREs, and other Platform teams, to ensure operability and maintainability of AI capabilities offered across the company.

Work Schedule: Full-time (40 hours per week) with flexible hours and remote work options available.

📝 Enhancement Note: N26 offers a high degree of autonomy and access to cutting-edge technologies, all while working with a friendly team of peers from diverse nationalities, life experiences, and family statuses. The company provides a competitive personal development budget, work-from-home budget, and other benefits to support employee growth and well-being.

📄 Application & Technical Interview Process

Interview Process:

Online Assessment: Complete an online assessment to evaluate your technical skills and problem-solving abilities.
Technical Deep Dive: Participate in a technical deep dive, focusing on your experience with infrastructure and reliability engineering, cloud-native development, and AI/ML-related services.
Behavioral & Cultural Fit: Engage in a behavioral and cultural fit interview to assess your communication skills, teamwork, and cultural alignment with N26.
Final Decision: The hiring team will make a final decision based on your technical skills, cultural fit, and overall potential for success in the role.

Portfolio Review Tips:

Highlight your experience in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services with relevant projects and case studies.
Showcase your programming skills with code samples or projects demonstrating your proficiency in Python, Go, or TypeScript.
Include any relevant testing methodologies, performance metrics, and optimization techniques used in your projects.
Tailor your portfolio to emphasize your ability to design, develop, and maintain scalable, secure, and compliant solutions for machine learning and generative AI use cases.

Technical Challenge Preparation:

Brush up on your knowledge of infrastructure and reliability engineering, deployment automation, monitoring, and incident response.
Familiarize yourself with cloud-native development, AWS infrastructure, and AI/ML-related services, such as SageMaker and Bedrock.
Prepare for technical questions related to networking, security, and compliance best practices in production environments.

ATS Keywords: Infrastructure Engineering, Reliability Engineering, Deployment Automation, Monitoring, Incident Management, Performance Tuning, Python, Go, TypeScript, Cloud-Native Development, AWS, Kubernetes, CI/CD, Terraform, Docker, Networking, Security, Compliance, AI/ML, Machine Learning, Generative AI, MLOps, SRE, Platform Engineering.

📝 Enhancement Note: To optimize your resume for the Site Reliability Engineer - AI Platform role at N26, focus on highlighting your relevant experience and skills in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services. Include any relevant projects, case studies, or certifications that demonstrate your proficiency in the required technologies and tools.

🛠 Technology Stack & Web Infrastructure

Frontend Technologies: (Not applicable for this role)

Backend & Server Technologies:

Programming Languages: Python, Go, TypeScript
Cloud Platform: AWS (Amazon Web Services)
Infrastructure-as-Code Tools: Terraform
Containerization: Docker
Orchestration: Kubernetes
CI/CD Pipelines: ArgoCD, GitHub Actions
AI/ML Platforms: SageMaker, Bedrock (or other AI/ML-related services)

Development & DevOps Tools:

Version Control: Git
Code Review: GitHub Pull Requests
Monitoring & Logging: Prometheus, Grafana, CloudWatch
Incident Management: PagerDuty, OpsGenie
Infrastructure Documentation: Terraform Cloud, AWS CloudFormation

📝 Enhancement Note: The technology stack for this role is primarily focused on backend and server technologies, with an emphasis on cloud-native development, AWS infrastructure, and AI/ML-related services. Familiarity with the listed technologies and tools is essential for success in this role.

👥 Team Culture & Values

Web Development Values:

Reliability: Ensure the availability, scalability, and performance of AI platform components through deployment, monitoring, and incident response.
Security & Compliance: Build secure, compliant, and scalable solutions that meet the highest standards for data protection and privacy.
Collaboration: Work closely with ML Engineers, SREs, and other Platform teams to ensure operability and maintainability of AI capabilities offered across the company.
Innovation: Contribute to the evolution of the AI platform, helping to build a foundation for reliable, scalable, and democratized access to Machine Learning and GenAI capabilities across N26.

Collaboration Style:

Cross-Functional Integration: Work closely with ML Engineers, SREs, and other Platform teams to ensure operability and maintainability of AI capabilities offered across the company.
Code Review Culture: Participate in code reviews, RFCs, and product discovery processes to ensure high-quality, maintainable, and well-documented code.
Knowledge Sharing: Share your knowledge and expertise with newer team members, fostering a culture of continuous learning and growth.

📝 Enhancement Note: The AI Platform team at N26 values collaboration, innovation, and a strong focus on reliability, security, and compliance. By joining this team, you will have the opportunity to work closely with experienced engineers in Machine Learning, Backend, and Platform Engineering, contributing to the evolution of the AI platform that's at the heart of the company's highest value bets.

⚡ Challenges & Growth Opportunities

Technical Challenges:

AI Platform Evolution: Contribute to the design and development of platform components that enable machine learning and generative AI use cases across the company, ensuring reliable deployment, maintenance, monitoring, and incident response.
Scalability & Performance: Build scalable, secure, and compliant solutions that can handle the increasing demands of machine learning and generative AI use cases across the company.
Emerging Technologies: Stay up-to-date with the latest developments in AI/ML and infrastructure technologies, integrating new tools and services into the AI platform as needed.
Cross-Functional Collaboration: Work closely with ML Engineers, SREs, and other Platform teams to ensure operability and maintainability of AI capabilities offered across the company, balancing the needs of various stakeholders.

Learning & Development Opportunities:

Technical Skill Development: Develop your expertise in AI infrastructure, working alongside experienced engineers in Machine Learning, Backend, and Platform Engineering.
Certifications & Training: Pursue relevant certifications and training opportunities to enhance your skills in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services.
Conferences & Community Involvement: Attend industry conferences, join relevant online communities, and engage with other professionals in the field to expand your knowledge and network.

📝 Enhancement Note: As a Site Reliability Engineer in the AI Platform team at N26, you will face various technical challenges related to the design, development, and maintenance of reliable AI platform components. By embracing these challenges and seeking out learning and development opportunities, you can grow your career in the AI infrastructure space and make a significant impact on the company's highest value bets.

💡 Interview Preparation

Technical Questions:

Infrastructure & Reliability Engineering: Describe your experience with deployment automation, monitoring, incident management, and performance tuning. Provide specific examples of how you have addressed these challenges in previous roles.
Cloud-Native Development & AWS: Explain your familiarity with cloud-native development and AWS infrastructure, including any experience with AI/ML-related services like SageMaker and Bedrock. Discuss any relevant projects or case studies that demonstrate your proficiency in these areas.
Networking, Security, & Compliance: Describe your working knowledge of networking, security, and compliance best practices in production environments. Provide examples of how you have ensured the security and compliance of AI platform components in previous roles.

Company & Culture Questions:

AI Platform Team: Research the AI Platform team's mission, values, and recent projects. Prepare questions that demonstrate your understanding of the team's goals and how your skills and experience can contribute to their success.
N26 Culture: Familiarize yourself with N26's company culture, values, and recent news. Prepare questions that showcase your alignment with the company's mission and your enthusiasm for working in a dynamic, innovative environment.

Portfolio Presentation Strategy:

Project Selection: Choose relevant projects from your portfolio that demonstrate your experience in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services.
Storytelling: Prepare a compelling narrative for each project, highlighting the challenges you faced, the solutions you implemented, and the outcomes you achieved.
Technical Deep Dive: Be prepared to dive deep into the technical aspects of your projects, explaining your approach to deployment automation, monitoring, incident response, and any other relevant aspects of infrastructure and reliability engineering.

📝 Enhancement Note: To prepare for the technical interview process for the Site Reliability Engineer - AI Platform role at N26, focus on honing your technical skills in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services. Research the AI Platform team's mission, values, and recent projects to demonstrate your understanding of the team's goals and your alignment with their culture.

📌 Application Steps

To apply for this Site Reliability Engineer - AI Platform position at N26:

Tailor Your Resume: Highlight your relevant experience and skills in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services. Include any relevant projects, case studies, or certifications that demonstrate your proficiency in the required technologies and tools.
Prepare Your Portfolio: Choose relevant projects that showcase your experience in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services. Prepare a compelling narrative for each project, highlighting the challenges you faced, the solutions you implemented, and the outcomes you achieved.
Research the Company & Team: Familiarize yourself with N26's company culture, values, and recent news. Research the AI Platform team's mission, values, and recent projects to demonstrate your understanding of the team's goals and your alignment with their culture.
Prepare for Technical & Behavioral Interviews: Brush up on your technical skills in infrastructure and reliability engineering, cloud-native development, and AI/ML-related services. Prepare for technical questions related to deployment automation, monitoring, incident response, networking, security, and compliance. Practice your communication skills and be ready to discuss your cultural fit with N26.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and web development/server administration industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

Site Reliability Engineer - AI Platform