We are seeking a highly skilled Backend Engineer to design, build, and maintain the core infrastructure for AI-powered applications. You will work closely with machine learning engineers, data scientists, and frontend developers to create scalable, secure, and efficient backend systems that enable cutting-edge AI capabilities.
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Key Responsibilities
- Design, develop, and maintain backend systems and APIs for AI-driven applications (for example, using a Python-based API with FastAPI or a Node.js server).
- Implement robust APIs that the front end will use, ensuring they are well-documented and secure.
- Optimize database architectures and data pipelines for efficient AI model training and inference.
- Implement secure authentication, authorization, and data protection mechanisms.
- Perform end-to-end testing of the pipeline to verify compatibility of all parts.
- Deep understanding of asynchronous processing and event-driven architectures to enhance system reliability and scalability.
- Collaborate with cross-functional teams to integrate AI models into production environments.
- Ensure system scalability, reliability, and performance through robust infrastructure design.
- Develop monitoring and logging tools for tracking system health and model performance.
- Write clean, efficient, and well-documented code following best practices.
Required Qualifications
- Bachelor's or Master’s degree in Computer Science, Software Engineering, or a related field.
- 3+ years of experience in backend development, with proficiency in server-side languages/frameworks – e.g., Python (Flask/Django/FastAPI) or JavaScript/TypeScript (Node.js, Express).
- Strong experience with RESTful APIs, GraphQL, and gRPC.
- Proficiency in database design and management (SQL and NoSQL databases such as PostgreSQL, MySQL, MongoDB, or Redis).
- Experience with cloud deployments such as AWS or Azure.
- Knowledge of containerization and orchestration tools (Docker, Kubernetes).
- Experience with distributed computing and microservices architectures.
- Strong problem-solving skills and ability to work in a fast-paced environment.
- Knowledge of message queues (Kafka, RabbitMQ) and event-driven architectures.
Preferred Qualifications
- Exposure to LLMs, vector databases, and AI inference optimization.
- Understanding of DevOps practices, CI/CD pipelines, and infrastructure as code (Terraform, Ansible).
- Familiarity with MLOps and AI model deployment pipelines is a plus.
