Full-Stack Engineer (Intern)

About the Role

Biz-Tech Analytics builds production-grade AI and data-driven solutions. We are looking for a Full-Stack Engineer who can work across application development, backend systems, cloud infrastructure, deployment, and system reliability. The ideal candidate enjoys building things end-to-end and can take ownership from development to production.

Key Responsibilities

• Design, develop, and maintain scalable full-stack web applications and internal platforms.
• Build and maintain robust backend services, REST APIs, and integrations.
• Develop responsive and functional frontend interfaces.
• Manage and improve cloud infrastructure, servers, networking, and deployment environments.
• Set up and maintain CI/CD pipelines for automated testing, deployment, and release management.
• Containerize applications using Docker and manage containerized workloads.
• Monitor application and infrastructure performance, availability, and reliability.
• Troubleshoot production issues and work on root-cause analysis and resolution.
• Implement logging, monitoring, alerting, and observability practices.
• Manage databases, data storage, backups, and access controls.
• Implement secure authentication, authorization, RBAC, and other application security practices.
• Collaborate with AI/ML engineers and other technical teams to deploy and integrate AI-driven applications and services.
• Optimize systems for performance, scalability, reliability, and cost efficiency.
• Automate repetitive development and infrastructure workflows.
• Maintain technical documentation and contribute to engineering best practices.

Requirements & Tech Stack

• Strong proficiency in at least one backend language such as Python, Node.js, Java, or Go.
• Experience with modern frontend technologies such as React, Next.js, or similar frameworks.
• Strong understanding of REST APIs, backend architecture, databases, and distributed systems.
• Hands-on experience with Docker and containerization.
• Experience with CI/CD tools and deployment pipelines.
• Working knowledge of cloud platforms such as AWS, Azure, or GCP.
• Good understanding of Linux, networking, servers, and system administration.
• Experience with relational databases such as PostgreSQL/MySQL.
• Understanding of Git, version control, branching, and collaborative development workflows.
• Familiarity with monitoring and logging tools.
• Strong debugging and problem-solving skills.

Good to Have

• Experience with Kubernetes or other container orchestration platforms.
• Experience with Terraform, Ansible, or other Infrastructure-as-Code tools.
• Experience deploying AI/ML applications or inference services.
• Familiarity with cloud-native architecture and microservices.
• Experience with authentication systems, RBAC, API security, and secrets management.
• Familiarity with Redis, message queues, or event-driven architectures.
• Experience working with NVIDIA GPUs, AI infrastructure, or model-serving systems.
• Exposure to MLOps workflows and machine learning deployment.

What We're Looking For

• Ability to work across both software development and infrastructure.
• Strong ownership and ability to take a feature or system from development to production.
• Ability to troubleshoot independently and solve problems systematically.
• Comfortable working in a fast-paced environment with changing requirements.
• Strong communication and collaboration skills.
• A practical, engineering-focused mindset with an emphasis on building reliable production systems.