Senior Backend Engineer

About Scality:
Scality solves organisations’ biggest data storage challenges — security, performance, and cost. Designed to provide the strongest form of immutability plus end-to-end cyber resilience, Scality solutions safeguard data at five core levels for unbreakable ransomware protection. Delivering utmost resilience, Scality makes storage infrastructures limitlessly scalable in all critical dimensions. The world’s most discerning companies trust Scality so they can grow faster and execute AI data-driven ideas quicker, while increasing efficiency and avoiding lock-in. Recognised as a leader by Gartner, Scality S3 object storage software is reliable, secure and sustainable.Follow us on Twitter and LinkedIn. Visit www.scality.com and our blog.
Mission:
To build and maintain the robust, scalable, and secure backend of our AI-driven infrastructure Analytics Platform. You will be the main contributor of the services that power our user-facing applications, ensuring seamless integration with our data pipeline and machine learning models. Your work is critical to the reliability and performance of the entire system, enabling the team to deliver actionable insights to our users.

Responsibilities :

• Backend Services & API Development: Design, build, and maintain scalable and resilient backend APIs to support the web application, integrate with AI models and establish endpoints for telemetry collection.
• You will work closely with the team to maintain a high level of automation for testing and deployment.
• MLOps Integration: Collaborate with the AI Engineer to productionize machine learning models. This includes building and maintaining systems for model deployment, monitoring, versioning, and retraining to ensure our AI solutions are reliable and scalable.
• Infrastructure & DevOps: Implement and manage automated infrastructure (Infrastructure as Code) and CI/CD pipelines to ensure smooth and frequent releases.
• Monitoring, Logging, and Alerting: Establish and manage comprehensive monitoring, centralized logging, and proactive alerting systems to ensure health, performance, and reliability. You will be responsible for identifying and resolving bottlenecks and potential issues before they impact users.
• Security & Data Governance: Implement and enforce robust security measures across all backend services, APIs, and infrastructure.
• Performance and Scalability: Continuously optimize the performance and scalability of the backend systems to handle growing data volumes and user traffic.

Skill Set :

• Programming Languages: Strong proficiency in backend programming languages such as Python, Go, or TS.
• API Development: Extensive experience in designing, building, and documenting RESTful (or GraphQL) APIs.
• Cloud & Infrastructure: Hands-on experience with Cloud Platform (GCP & AWS), especially Vertex, BigQuery, Cloud Run, and GKE. Proficiency with Infrastructure as Code tools like Terraform.
• CI/CD & DevOps: Solid understanding and practical experience with CI/CD principles and tools (e.g., GitLab CI, GitHub Actions). Experience with containerization using Docker and orchestration with Kubernetes.
• Databases: Experience with both SQL and NoSQL databases.
• Monitoring & Observability: Familiarity with monitoring tools like Prometheus, Grafana, and logging platforms.
• Security: Deep expertise of security, authentication (OAuth, JWT), authorization, and data encryption.
• Soft Skills: Strong problem-solving abilities, excellent communication skills, and a collaborative mindset to work effectively in a T-shaped team.

Additional Expertise :

• SaaS Application Experience: Professional experience working on and contributing to Software as a Service (SaaS) applications.
• Interest in AI & LLM Agentic Applications: A strong interest in artificial intelligence, machine learning, and hands-on experience or a keen interest in building AI agentic applications using Large Language Models (LLMs) is a significant plus.
• Proficiency with AI Coding Assistants: Demonstrated proficiency in leveraging the latest AI coding assistants and tools to enhance development efficiency and code quality.
• Distributed Systems Knowledge: Understanding of concepts related to distributed computing, consensus algorithms, and fault tolerance.