Software Engineer, Backend

10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs, AI unicorns, Fortune 10 companies, and leading global technology platforms. In this role, you will design and implement backend services and APIs, collaborate with various teams to bring AI features to production, and ensure security and scalability in the deployment of services.

Responsibilities:

• Design and implement highly reliable, distributed, backend services and APIs that are secure, scalable, and maintainable, primarily using Python and Kotlin
• Work closely with researchers, security engineers, and product teammates to bring AI-driven features from concept to production
• Apply best practices for authentication, authorization, encryption, and data protection throughout the stack
• Integrate and optimize advanced AI/ML models within backend architectures
• Monitor and improve performance, reliability, and resource efficiency to support growth
• Deploy and manage services on Google Cloud Platform (GCP) such as Cloud Run, Vertex AI, and API Gateway with an emphasis on ensuring scalability, reliability, and efficient resource utilization
• Participate in code reviews, testing, and deployment processes to maintain high standards of quality and security; and
• Drive other critical initiatives

Requirements:

• Degree in Computer Science, Engineering, or related field — or equivalent professional experience
• 3+ years of hands-on backend development in production environments
• Proficiency in backend programming languages such as Python, Java, Kotlin, Node.js, or Go and experience building secure systems, APIs, and microservices
• Strong understanding of security best practices, including authentication methods (OAuth, JWT), encryption, and secure API development; knowledge of common attack vectors (SQL injection, privilege escalation, DDoS) and effective mitigation strategies
• Experience with cloud infrastructure (AWS, GCP) and secure deployment practices, including containerization (Docker, Kubernetes)
• Experience effectively communicating complex engineering topics to both technical and non-technical stakeholders
• Familiarity with modern DevOps practices, including test automation, CI/CD pipelines, and infrastructure-as-code practices
• Experience designing and building end-to-end backend systems, from architecture and data modeling to deployment, scaling, and monitoring
• Experience integrating and optimizing AI models (e.g., NLP, vision, multimodal systems) within backend services
• Familiarity with SQL and NoSQL databases; experience with secure data management