- Company Name
- Eximium Talent
- Job Title
- Full Stack Engineer
- Job Description
-
Job Title: Full Stack Engineer (Intern)
Role Summary: Design, develop, and maintain AI‑powered SaaS applications, driving end‑to‑end functionality from backend services to responsive front‑end interfaces, while managing cloud deployments and CI/CD pipelines.
Expectations: Deliver production‑ready features, collaborate with cross‑functional teams, iterate on AI integrations, and contribute to reliability, scalability, and usability of client‑facing products.
Key Responsibilities:
- Build and maintain full‑stack SaaS applications using Node.js and/or Django.
- Develop responsive, UX‑focused front‑end interfaces (React/Angular/Vue).
- Design and manage databases (SQL/NoSQL) and implement data models.
- Set up, automate, and monitor CI/CD pipelines with Docker, GitHub Actions, or similar.
- Deploy and manage cloud infrastructure (AWS, GCP, Azure) and container orchestration.
- Integrate AI services (OpenAI, Hugging Face, other ML APIs) into production workflows.
- Debug, test, and optimize code for performance and security.
- Work with product, design, and QA teams to iterate on features and ensure high quality.
- Suggest and prototype improvements to scalability, reliability, and user experience.
Required Skills:
- Strong foundation in full‑stack web development (backend + frontend).
- Proficiency in Node.js and/or Django (Python).
- Experience with modern JavaScript/TypeScript frameworks (React, Vue, Angular).
- Knowledge of SQL and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB).
- Hands‑on Docker, CI/CD tooling, and cloud platform usage (AWS/GCP/Azure).
- Ability to integrate external APIs, including AI/ML services (OpenAI, Hugging Face).
- Solid debugging, testing (unit, integration), and performance optimization skills.
- Good communication and teamwork in an agile environment.
Nice to Have:
- Prior exposure to AI/ML pipelines or experimenting with ML frameworks (TensorFlow, PyTorch).
- Experience building or scaling SaaS products.
Required Education & Certifications:
- Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent practical experience).
- Relevant certifications (e.g., AWS Certified Developer, Docker Certified Associate) are a plus.