Software Engineer - Backend

About the Role

Backend Engineer

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)
• API Development: Implement robust APIs that the front end will use. Understanding of MVC framework and good hold on OOPS principles. The endpoints should be 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.
• Integration Testing: Perform end-to-end testing of the pipeline. The Back End Engineer should simulate the full run (from model input to result output) to verify that all parts are compatible. This might involve writing a simple script or using an API client to call the endpoints in sequence and checking that the final output matches expected results
• Event Driven Architecture: Deep understanding of asynchronous processing, including managing message ordering, idempotency, and dead-letter queues (DLQs) to ensure system reliability.

Experience

• in decoupling microservices through event-based communication to improve system scalability and fault tolerance
• 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). Able to quickly set up RESTful APIs and handle request/response cycles.
• 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.
• Experience with setting up logging/monitoring frameworks (eg. Sentry)
• 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.

Why Join Us?

• Work on cutting-edge AI applications with a talented and passionate team.
• Opportunity to innovate and solve real-world challenges using AI.
• Competitive compensation, benefits, and career growth opportunities.
• Flexible working environment and the latest tools & technologies.