This is a remote full-time paid internship role for a Technology Intern. As a Tech Intern, you will be responsible for Develop features - build new features for Echo using Python. Data Analysis - run market research analysis using Echo’s toolkit to deliver projects for our clients. Frontend - Build UI in angular. Data science - Train and finetune AI/ML models Prompt Engineering - create and improve prompt chains Salary : Rs.10k/pm Duration : 2-6 months Qualifications Strong Python skills Strong communication skills Full stack experience Ability to work independently and remotely Experience with data analysis Proficiency in Google Sheets Enthusiasm for building products 0 to 1 Must-have qualifications Should have laptop to work from. Strong Python experience and some Experience in Frontend frameworks like React/Angular Leetcode experience Preferred qualifications Tons of original projects done in college. Familiarity with Open AI and other LLMs PSA : This is ideal for final year students who have already been placed and are looking for 2-6 month internship. You will earn a ton of skills in this role. Show more Show less

Role: Prompt Engineer (Full-time Internship, Remote) This is a remote full-time paid internship for a Prompt Engineer. You will help us push the boundaries of what LLMs can do by designing, testing, and optimizing individual prompts as well as multi-step prompt chains to solve complex tasks. Responsibilities Prompt Crafting : Design, edit, and refine prompts for different use cases and models. Prompt Chaining : Break down complex tasks into smaller subtasks and build effective multi-step prompt workflows (e.g., summarization → critique → rewrite). Benchmarking & Evaluation : Use Python to run automated performance benchmarks based on KPIs like accuracy, cost, and latency. Iterative Improvement : Run A/B tests, gather output samples, and tweak prompts based on failure cases and edge conditions. KPI Optimization : Ensure prompt chains meet predefined goals like output quality, relevance, length, and compute cost. Model Awareness : Stay updated with the latest in GPT, Claude, Gemini, and open-source LLMs. Tooling & Automation : Build or use lightweight tooling for prompt testing, logging, and result comparison. Documentation : Maintain a structured prompt logbook with evaluations, learnings, and chain architecture. Salary: Rs.15,000/month Duration : 3–6 months Must-Have Qualifications Strong Python scripting and automation experience. Experience using OpenAI or other LLM APIs. Understanding of prompt chaining or multi-step reasoning with LLMs. Comfort with debugging and improving prompts using test inputs and edge cases. Strong communication and analytical skills. Familiarity with basic evaluation techniques (BLEU, ROUGE, token count, etc.). Nice-to-Have LangChain or similar framework experience. Experience working with vector DBs, retrieval-augmented generation (RAG), or memory components. Knowledge of how to manage context windows and output formatting across models. Open-source contributions or published prompt collections. Ideal For Final-year students or recent grads curious about AI/LLMs and looking to develop real-world prompt engineering and model optimization skills. You’ll work closely with founders to build robust, high-performing AI workflows for production-grade products.

Role: Prompt Engineer (Full-time Internship, Remote) This is a remote full-time paid internship for a Prompt Engineer. You will help us push the boundaries of what LLMs can do by designing, testing, and optimizing individual prompts as well as multi-step prompt chains to solve complex tasks. Responsibilities Prompt Crafting : Design, edit, and refine prompts for different use cases and models. Prompt Chaining : Break down complex tasks into smaller subtasks and build effective multi-step prompt workflows (e.g., summarization → critique → rewrite). Benchmarking & Evaluation : Use Python to run automated performance benchmarks based on KPIs like accuracy, cost, and latency. Iterative Improvement : Run A/B tests, gather output samples, and tweak prompts based on failure cases and edge conditions. KPI Optimization : Ensure prompt chains meet predefined goals like output quality, relevance, length, and compute cost. Model Awareness : Stay updated with the latest in GPT, Claude, Gemini, and open-source LLMs. Tooling & Automation : Build or use lightweight tooling for prompt testing, logging, and result comparison. Documentation : Maintain a structured prompt logbook with evaluations, learnings, and chain architecture. Salary: Rs.20,000/month Duration : 3–6 months Must-Have Qualifications Strong Python scripting and automation experience. Experience using OpenAI or other LLM APIs. Understanding of prompt chaining or multi-step reasoning with LLMs. Comfort with debugging and improving prompts using test inputs and edge cases. Strong communication and analytical skills. Familiarity with basic evaluation techniques (BLEU, ROUGE, token count, etc.). Nice-to-Have LangChain or similar framework experience. Experience working with vector DBs, retrieval-augmented generation (RAG), or memory components. Knowledge of how to manage context windows and output formatting across models. Open-source contributions or published prompt collections. Ideal For Final-year students who have semester break for internship or recent grads ambitious about AI/LLMs and looking to develop real-world prompt engineering and model optimization skills. You’ll work closely with founders to build robust, high-performing AI workflows for production-grade products.

Role: AI Engineer Intern (Full-time Internship, Remote) This is a remote full-time paid internship for an AI Engineer. You will help us push the boundaries of what LLMs can do by designing, testing, and optimizing prompts, building multi-step prompt pipelines, writing scaffolding code around LLM calls, benchmarking outputs, and integrating AI features into real-world products using Python and NLP techniques. Responsibilities Prompt Crafting: Design, edit, and refine prompts for different use cases and models. Prompt Chaining: Break down complex tasks into smaller subtasks and build effective multi-step prompt workflows (e.g., summarization → critique → rewrite). Benchmarking & Evaluation: Use Python (scripts and notebooks) to run automated performance benchmarks based on KPIs like accuracy, cost, and latency. Feature Building: Write Python scaffolding to integrate LLM calls into usable product features and pipelines. Hybrid NLP: Use traditional NLP techniques (e.g., regex, spaCy, NLTK) alongside LLMs to improve output quality, preprocessing, or efficiency. Iterative Improvement: Run A/B tests, gather output samples, and tweak prompts or logic based on failure cases and edge conditions. KPI Optimization: Ensure prompt chains and model outputs meet goals like quality, relevance, length, and compute cost. Model Awareness: Stay updated with the latest in GPT, Claude, Gemini, and open-source LLMs. Tooling & Automation: Build or use lightweight tooling for prompt testing, logging, and result comparison. Documentation: Maintain a structured prompt and workflow logbook with evaluations, learnings, and architecture. Salary: Rs.15,000/month Duration: 3–6 months Must-Have Qualifications Strong Python scripting and automation experience. Experience using OpenAI or other LLM APIs. Ability to build small-scale tools or workflows that integrate and manage prompt-based logic. Understanding of prompt chaining or multi-step reasoning with LLMs. Familiarity with Jupyter/Colab for fast prototyping. Awareness of basic NLP techniques and when to combine them with LLM outputs. Comfort with debugging and improving outputs using test inputs and edge cases. Strong communication and analytical skills. Familiarity with basic evaluation techniques (BLEU, ROUGE, token count, etc.). Nice-to-Have LangChain or similar framework experience. Experience working with vector DBs, retrieval-augmented generation (RAG), or memory components. Knowledge of managing context windows, formatting outputs, or chaining across models. Open-source contributions, AI blog posts, or published prompt collections. Ideal For Final-year students who have semester break for internship or recent grads ambitious about AI/LLMs and looking to develop real-world AI engineering, prompt design, and hybrid NLP-LLM skills. You’ll work closely with founders to build robust, high-performing AI workflows and features for production-grade products. PPO offer post successful internship.