Ai Full Stack Engineer

Job Description


Job Summary


Key Responsibilities

• Design and develop scalable full-stack web applications using Next.js/React.js and Python .
• Develop robust backend services, REST APIs, and integrations using Python frameworks such as FastAPI, Flask, or Django .
• Design, develop, and optimize databases including PostgreSQL, MySQL, MongoDB , or similar technologies.
• Integrate LLMs and Generative AI APIs into web applications.
• Work with AI/LLM-based features such as prompt engineering, RAG, embeddings, vector databases, and AI-powered workflows .
• Develop and maintain APIs for communication between frontend, backend, databases, and AI services.
• Optimize application performance, scalability, security, and reliability.
• Work with third-party AI services and APIs such as OpenAI or other LLM platforms .
• Collaborate with developers, product teams, and stakeholders to understand requirements and deliver solutions.
• Debug, troubleshoot, and improve existing applications and AI integrations.
• Stay updated with the latest developments in AI, LLMs, Generative AI, and full-stack technologies .

Requirements

Required Skills

• 5+ years of professional experience in software/full-stack development.
• Strong hands-on experience with Next.js and React.js .
• Strong proficiency in Python .
• Good experience with REST APIs and backend development .
• Strong knowledge of SQL and database concepts .
• Experience with PostgreSQL / MySQL / MongoDB or similar databases.
• Practical experience working with LLMs / Generative AI .
• Experience integrating Ai/llm APIs into applications.
• Understanding of Prompt Engineering, RAG, embeddings, and vector databases is highly preferred.
• Good understanding of software development lifecycle and coding best practices.
• Strong problem-solving and analytical skills.

Preferred / Good-to-Have Skills

• Experience with FastAPI, Flask, or Django .
• Experience with LangChain, LlamaIndex, or similar LLM frameworks .
• Knowledge of Pinecone, FAISS, Chroma, Weaviate , or other vector databases.
• Experience with cloud platforms such as AWS, Azure, or GCP .
• Knowledge of Git/GitHub and CI/CD.
• Experience building production-ready AI-powered applications.

Education


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