Job
Description
Role Overview: As a member of the Cisco Networking Tooling team, you will be responsible for designing, developing, and maintaining full-stack applications using technologies such as Node.js, React, Python, and modern cloud platforms like AWS, Azure, and GCP. Your impact will enhance efficiency, collaboration, resource management, innovation, and scalability within Engineering and Operations by providing agile and resilient tooling. Working closely with front-end and back-end developers, data scientists, and UX/UI designers, you will contribute to creating seamless user experiences. Your strong problem-solving skills and ability to work in an agile environment will be key to optimizing code for performance, scalability, and maintainability. Key Responsibilities: - Design, develop, and maintain full-stack applications using Node.js, React, Python, and modern cloud platforms (AWS, Azure, GCP). - Integrate Generative AI models (LLMs, text/image/audio generation, etc.) into web applications. - Optimize AI workflows and APIs for scalability, performance, and security. - Work with LLM frameworks such as LangChain, LangGraph, Hugging Face & OpenAI API. - Manage code versions and ensure collaborative coding practices using Git. Participate in code reviews and implement CI/CD best practices. - Ensure best practices in CI/CD, DevOps, and cloud infrastructure management. - Develop and manage RESTful and GraphQL APIs for AI model integration. - Troubleshoot and resolve issues with both cloud infrastructure and application code. Optimize code for performance, scalability, and maintainability. - Conduct code reviews, testing, and performance optimizations. Qualification Required: - Experience in Full Stack Engineer (Node.js, React, TypeScript, Python). - Hands-on experience with Generative AI frameworks and APIs (e.g., OpenAI, Hugging Face, Stability AI). - Strong knowledge of database technologies (MongoDB Atlas, SQL, NoSQL, PostgreSQL). - Proficiency in cloud services (AWS, GCP, Azure) and containerization (Docker, Kubernetes). - Understanding of LLMs, model fine-tuning, and vector databases (e.g., Pinecone, FAISS, ChromaDB). - Experience in MLOps and AI model deployment is a plus. - Familiarity with Retrieval-Augmented Generation (RAG) pipelines. - Experience with GraphQL, WebSockets, and real-time applications. - Knowledge of AI ethics, bias mitigation, and responsible AI development. - Knowledge and experience using API suites of the following cloud-based tools: Aha, Jira is desired. - Good communications skills and good knowledge of English language. - Team player with the ability to get up to speed quickly and work with minimum guidance.,