Job Description Design and build smart automation workflows using n8n , Zapier , and Make.com . Integrate APIs and connect third-party apps to streamline business processes. Use LLMs (e.g., OpenAI, Cohere) for tasks like summarization, data extraction, and decision logic. Build RAG pipelines with vector databases like Pinecone , ChromaDB , or Weaviate . Develop and test autonomous agents using LangChain , AutoGen , or similar frameworks. Write clean, modular code in Python or JavaScript to support custom workflow logic. Prototype ideas quickly and ship real features used in production environments. Document your workflows and collaborate with developers, consultants, and product teams. Key Skills Final-year students: Only final year students in Computer Science, AI/ML, Data Science, Information Systems, or related fields., who are willing to work full time after internship. Curiosity & Initiative : You love experimenting with new tools/technologies and aren’t afraid to break things to learn. Basic to Intermediate Coding Skills : Comfortable writing Python or JavaScript/TypeScript. Able to read API docs and write modular code. Familiarity (or willingness to learn) Workflow Platforms : Exposure to n8n, Zapier, Make.com, or similar; if you haven’t used n8n yet, we’ll help you onboard. API Knowledge : Understanding of RESTful APIs, JSON, authentication mechanisms. Interest in AI/LLMs : You know the basics of LLMs or are eager to dive in—prompt engineering, embeddings, RAG concepts. Problem-Solving Mindset : You can break down complex tasks into smaller steps, map flows, and foresee edge cases. Communication & Documentation : You can explain your workflows, document steps, and write clean README/instructions. Team Player : Open to feedback, collaborate in agile/scrum-like setups, and help peers troubleshoot.

Job Description Design and build smart automation workflows using n8n , Zapier , and Make.com . Integrate APIs and connect third-party apps to streamline business processes. Use LLMs (e.g., OpenAI, Cohere) for tasks like summarization, data extraction, and decision logic. Build RAG pipelines with vector databases like Pinecone , ChromaDB , or Weaviate . Develop and test autonomous agents using LangChain , AutoGen , or similar frameworks. Write clean, modular code in Python or JavaScript to support custom workflow logic. Prototype ideas quickly and ship real features used in production environments. Document your workflows and collaborate with developers, consultants, and product teams. Key Skills Final-year students: Only final year students in Computer Science, AI/ML, Data Science, Information Systems, or related fields., who are willing to work full time after internship. Curiosity & Initiative : You love experimenting with new tools/technologies and aren’t afraid to break things to learn. Basic to Intermediate Coding Skills : Comfortable writing Python or JavaScript/TypeScript. Able to read API docs and write modular code. Familiarity (or willingness to learn) Workflow Platforms : Exposure to n8n, Zapier, Make.com, or similar; if you haven’t used n8n yet, we’ll help you onboard. API Knowledge : Understanding of RESTful APIs, JSON, authentication mechanisms. Interest in AI/LLMs : You know the basics of LLMs or are eager to dive in—prompt engineering, embeddings, RAG concepts. Problem-Solving Mindset : You can break down complex tasks into smaller steps, map flows, and foresee edge cases. Communication & Documentation : You can explain your workflows, document steps, and write clean README/instructions. Team Player : Open to feedback, collaborate in agile/scrum-like setups, and help peers troubleshoot.