Full Stack Engineer

Responsibilities:
Collaborating with senior engineers to understand project requirements and contribute to ongoing development tasks.
Writing clean, efficient, and maintainable code across frontend or backend modules, depending on project needs.
Debugging and troubleshooting issues by analysing logs, identifying root causes, and implementing effective fixes.
Working on system design components, including understanding architecture diagrams and contributing to scalable solutions.
Building and consuming RESTful APIs or GraphQL services to integrate various system components.
Developing user interfaces using modern frontend frameworks like React, Angular, or Vue, and optimising UI performance.
Managing databases by writing queries, optimising data structures, and working with PostgreSQL, MongoDB, or vector databases.
Contributing to cloud deployments using AWS, GCP, or Azure, and assisting in CI/CD pipeline maintenance.
Using containerization and orchestration tools such as Docker & Kubernetes for application builds and deployments.
Working with automation tools like Selenium or Playwright for testing and quality assurance.
Implementing AI/ML workflows, including RAG pipelines, embeddings, model inferencing, and vector search when required.
Participating in code reviews, following coding standards, and continuously improving development practices.
Documenting technical tasks, workflows, and solutions in an organised and clear manner.
Staying updated with emerging technologies and proactively applying relevant innovations to ongoing projects.
Taking ownership of assigned modules, ensuring timely delivery with minimal supervision.
The core requirements for the job include the following:
Core technical skills:
Strong programming fundamentals (data structures & algorithms).
Proficiency in at least one programming language.
Frontend frameworks: React, Angular, Vue.js, Next.js .
Backend development: Node.js/.NET, RESTful APIs, GraphQL.
Database skills: PostgreSQL, MongoDB, SQL queries.
Understanding of Vector Databases (Pinecone, Weaviate, Milvus, Redis Vector, and Supabase Vector).
Cloud platforms: AWS/GCP/Azure.
DevOps basics: CI/CD, Docker, Kubernetes.
Automation & testing tools: Selenium, Playwright.
Knowledge of Redis, caching, message queues (RabbitMQ, Kafka).
AI/ML and modern architecture:
Basic understanding of RAG, embeddings, and model inference.
Familiarity with tools like LangGraph and Hugging Face.
Understanding of vector search concepts.
System design and architecture:
Fundamentals of building scalable systems.
Understanding microservices, APIs, caches, load balancing, etc.
Networking basics: HTTP/HTTPS, DNS, TCP/IP, API communication models.
Core soft skills:
Strong communication and clarity of thought.
Debugging and troubleshooting mindset.
Creative, out-of-the-box problem-solving.
Ability to work independently and take ownership.
Fast thinking and high execution speed.
Optimisation mindset (performance, scalability).
Collaboration and teamwork.

Experience
0-1 yrs