Dimaag AI - Full Stack Architect - React.js/Node.js/Python (8-12 yrs)

Job Description :

We are looking for an experienced Full Stack Architect who can lead a team, mentor juniors, hands-on develop, & maintain secure, scalable applications.

The ideal candidate will have hands-on experience with leading a team in both front-end and back-end technologies, particularly Reactjs, node.js, Python, PostgreSQL, & MongoDB, and will work closely with the management to build and optimize web applications that handle large-scale data and AI-driven solutions.

Key Responsibilities :

- lead a small / mid-sized team of frontend and backend developers

- Develop and maintain web applications using React.js for frontend, node.js / Python for backend and AI/ML Integration

- Design, build, and optimize scalable and robust backend systems.

- Collaborate with cross-functional teams to define, design, and deliver new features.

- Work on event streaming technologies to manage large-scale data (videos, images).

- Ensure the performance, quality, and responsiveness of applications.

- Troubleshoot and debug applications to optimize performance.

- Write clean, maintainable, and scalable code following best practices.

- Collaborate with the DevOps team to deploy, monitor, and maintain applications.

Required Skills & Qualifications:

- Bachelor of Engineering - Computer Science and related fields

- 8+ years of experience as a Full Stack Developer.

- Proficiency in React.js (frontend), node.js (backend), Python (backend), MongoDB, PostgreSQL.

- Experience with event streaming technologies (e.g, Kafka, Redis) and handling large-scale data.

- Strong knowledge of backend system design and development.

- Experience with databases (SQL/NoSQL) and APIs.

- Familiarity with cloud platforms (AWS, GCP, or Azure).

- Experience with version control (Git) and CI/CD pipelines.

- Strong problem-solving and debugging skills.

- Ability to work collaboratively in a fast-paced environment.

Preferred :

- Experience with AI/ML frameworks and integrations (e.g, TensorFlow, PyTorch).

- Familiarity with real-time data processing and microservices architecture.

- Experience with containerization technologies (Docker, Kubernetes)