Job Title:Senior Full Stack Developer (RAG-based AI Application Development)
Experience:5-8 Years
Job Description:
We are seeking a highly skilled and experienced Senior Full Stack Developer with a strong background in developing Retrieval-Augmented Generation (RAG) based AI applications. The ideal candidate will have 5-8 years of hands-on experience in full stack development, with a proven track record of building, deploying, and maintaining advanced AI-driven solutions. You will work closely with data scientists, AI engineers, and product teams to design and implement scalable, robust, and high-performance applications that leverage the latest advancements in RAG and generative AI.
Key Responsibilities:
- Design, develop, and maintain end-to-end web applications with a focus on RAG-based AI solutions.
- Collaborate with AI/ML engineers to integrate retrieval and generation models into production systems.
- Architect scalable backend services and APIs to support AI-driven features.
- Develop intuitive and responsive front-end interfaces using modern JavaScript frameworks (e.g., React, Angular, or Vue.js).
- Optimize application performance, scalability, and security.
- Implement best practices for code quality, testing, and continuous integration/deployment (CI/CD).
- Mentor junior developers and participate in code reviews.
- Stay up-to-date with the latest trends in AI, RAG, and full stack development.
Required Skills & Qualifications:
- Bachelor's or Master's degree in Computer Science, Engineering, or related field.
- 5-8 years of professional experience as a Full Stack Developer.
- Strong proficiency in backend technologies (e.g., Node.js, Python, Java, or Go).
- Experience with frontend frameworks (e.g., React, Angular, Vue.js).
- Deep understanding of RAG (Retrieval-Augmented Generation) architectures and their application in AI systems.
- Hands-on experience integrating LLMs (e.g., OpenAI GPT, Llama, etc.) with retrieval mechanisms (e.g., vector databases, Elasticsearch, Pinecone, FAISS).
- Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Experience with RESTful and GraphQL APIs.
- Strong knowledge of database systems (SQL and NoSQL).
- Excellent problem-solving, communication, and teamwork skills.
Preferred Qualifications:
- Experience with MLOps tools and workflows.
- Familiarity with data pipelines and ETL processes.
- Prior experience in deploying and scaling AI/ML models in production environments.
- Contributions to open-source AI or RAG projects.
