Senior Full Stack Developer

2 weeks ago

Bengaluru India Metawurks Full time

Job Description 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.

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