Key skills
PythonCybersecuritySecure API DevelopmentAI Model IntegrationCloud InfrastructureSQLNoSQLDevOps PracticesCommunication SkillsJavaGoKotlinAIMLNLPNode.jsAWSGCPKubernetesDockerOAuthJWTCI/CD
About this role
10a Labs is the safety and threat-intelligence layer trusted by frontier AI labs and Fortune 10 companies. They are seeking a Backend Software Engineer to design and implement secure, scalable backend services and APIs, working closely with researchers and security engineers to integrate AI-driven features into production.
Responsibilities:
- Design and implement backend services and APIs that are secure, scalable, and maintainable, primarily using Python
- 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
- Participate in code reviews, testing, and deployment processes to maintain high standards of quality and security
Requirements:
- Degree in Computer Science, Engineering, or related field — or equivalent professional experience
- 3+ years of professional, 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 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
- 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