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Full-Stack Engineer (Intern)

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Description

About Biz-Tech Analytics


At Biz-Tech Analytics, we build production-grade AI and data-driven solutions that help businesses turn complex data into actionable intelligence. Our work spans AI training data, annotation workflows, automation, and scalable technology infrastructure supporting real-world AI systems.


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 is someone who 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 when required.
  • 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 appropriate 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.

Required Skills

  • 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 and familiarity with NoSQL databases is a plus.
  • 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

  • Someone who can 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.

Why Join Biz-Tech Analytics?

  • Work on real-world AI, automation, and data-driven technology.
  • Build and manage systems that support production AI workflows.
  • Work closely with engineering, AI/ML, and business teams.
  • Take meaningful ownership of infrastructure and product development.
  • Opportunity to work across Full-Stack Engineering, DevOps, Cloud, and AI infrastructure.

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