Back End Engineer-AI Labs

Purpose/Objective

The Backend Engineer – AI Labs is responsible for developing, optimizing, and maintaining backend services, APIs, and databases that support AI-driven applications. Reporting to the Lead - Backend Engineering, this role focuses on building scalable, secure, and high-performance backend systems, integrating AI models into production workflows, and collaborating with frontend, DevSecOps, and data science teams to ensure seamless data flow and API performance.

Key Responsibilities of Role

Back End Engineer-AI Labs Backend Development & API Implementation: Develop and maintain scalable backend services that ensure reliability and security for AI-powered applications. Build and optimize RESTful & GraphQL APIs, enabling efficient communication between AI models and user interfaces. Implement microservices-based architecture using FastAPI, NestJS, or similar frameworks, ensuring modular and scalable backend solutions. Ensure API reliability and efficiency, minimizing latency through caching, asynchronous processing, and load balancing. Integrate authentication and authorization mechanisms (OAuth, JWT, RBAC) to secure API endpoints. Database & Storage Management: Manage and optimize SQL, NoSQL, and Vector databases, ensuring efficient data storage and retrieval. Improve database query performance through indexing, caching, and partitioning strategies. Ensure high availability and data consistency by implementing backup, replication, and failover mechanisms. Work with AI engineers to store, process, and retrieve large datasets, supporting AI ML workloads. AI Model Integration & Performance Optimization: Deploy AI ML models into backend workflows, ensuring low-latency and efficient model inference. Optimize data pipelines for AI applications, reducing response times and ensuring smooth real-time processing. Implement event-driven architectures to handle AI model triggers, ensuring efficient request handling. Collaborate with AI engineers to refine model-serving performance and inference scalability. Security, Scalability & Performance Optimization: Ensure backend security by implementing encryption, authentication, and compliance measures. Optimize backend performance for handling high-throughput AI-driven requests with low latency. Develop monitoring and logging mechanisms, ensuring real-time issue detection and debugging. Support disaster recovery and failover planning, maintaining backend resilience in production. Cross-Functional Collaboration & Continuous Improvement: Work closely with frontend engineers to ensure seamless API integration and user experience. Collaborate with DevSecOps teams to optimize backend deployments, security enforcement, and CI CD processes. Participate in agile development cycles, ensuring timely backend feature releases. Stay updated on backend technologies, contributing to process improvement and innovation. Key Stakeholders - Internal Frontend Developers DevOps & Cloud Teams Product Managers & Business Teams Security & Compliance Teams Key Stakeholders - External API Vendors & Cloud Providers Third-Party Integration Partners Open-Source Communities

Technical Competencies

AI & Computer Vision Integration-SDIL,Backend Development & API Design-SDIL,Database Management & Optimization-SDIL,Performance & Security Testing-SDIL,Test Automation & Framework Development-SDIL

Qualifications and Experience

Educational Qualification: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or related fields. Certification: AWS Certified Developer – Associate Google Professional Cloud Developer Microsoft Azure Developer Associate. Certified Kubernetes Administrator (CKA). Advanced Backend Development & API Security Certifications (Udemy, Coursera, LinkedIn Learning). Work Experience (Range of years): 1-10 years years of experience in backend development, distributed systems, and API design. Proficiency in backend programming languages such as Python, Java, or Go. Strong expertise in database management using PostgreSQL, MySQL, MongoDB, or Cassandra. Experience with containerization, cloud services, and CI CD pipelines.