À propos
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.
Nice to Have
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
Salary Range: $105K–$125K, depending on experience and location
Bonus: Performance-based annual bonus
Professional Development: Support for conferences, continuing education, or leadership training
Work Environment: Fully remote, U.S.-based
Time Off: Generous PTO and paid holiday schedule
Qualifications
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
Overview Interested in building your career at 10a Labs? Learn more about joining our team and opportunities as they arise.
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Compétences linguistiques
- English
Avis aux utilisateurs
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