Junior AI Developer

Role & Responsibilities

We are looking for a curious and passionate Junior AI Developer to join our growing AI team. You will help build AI-powered applications using LLMs, RAG architectures, and Agentic AI frameworks to solve real-world business problems. You will work closely with senior AI engineers to transform business requirements into practical AI solutions. We value learning ability, AI enthusiasm, and hands-on projects over professional experience.

Key Responsibilities

• Assist in building chatbots, RAG applications, AI agents, and document intelligence solutions (e.g., extracting data from invoices and contracts)
• Build AI agents and multi-step workflows that automate business processes
• Write, test, and refine prompts, including structured (JSON) outputs and tool/function calling
• Prepare data for AI applications through document parsing, chunking, embedding generation, and vector database storage
• Work with enterprise knowledge bases, SQL databases, vector databases, and APIs to retrieve and process data
• Build and integrate AI features into web and mobile applications using Python, FastAPI, REST APIs, and JSON
• Create test sets and evaluations to measure output accuracy, hallucinations, and retrieval quality
• Track cost, latency, and errors using tracing, logging, and observability tools
• Follow secure practices, including API key protection, user data security, and prompt injection prevention
• Write clean, documented code and follow Git-based workflows, including code reviews
• Learn best practices from senior AI engineers and stay updated on new AI tools and frameworks

Required Skills & Qualifications

• 0-1 year of experience (Freshers can apply)
• Degree in AI / Machine Learning (preferred) or Computer Science / IT
• Strong foundation in Python (preferred) or similar backend languages, with knowledge of API development, and basic async programming
• Understanding of Generative AI, Prompt Engineering, RAG, and AI Agent concepts
• Understanding of LLM fundamentals, including tokenization, context windows, temperature, sampling, embeddings, and a high-level view of transformer architecture
• Hands-on experience with LLM APIs (OpenAI, Anthropic, or Gemini), including structured outputs and tool calling
• Basic understanding of Model Context Protocol (MCP), including tools, resources, and connecting LLMs to external systems
• Exposure to frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, OpenAI Agents SDK, or similar
• Understanding of vector databases (FAISS, ChromaDB, pgvector), embeddings, and semantic search
• Basic knowledge of SQL, REST APIs (FastAPI/Flask), JSON, and software development fundamentals
• Familiarity with Git
• At least one AI certification or online course (e.g., NPTEL, Hugging Face, IBM, NASSCOM FutureSkills Prime, GUVI, AWS, Microsoft, or NVIDIA)
• Hands-on AI projects from academics, internships, hackathons, or personal work, with a GitHub or portfolio link
• Strong problem-solving and communication skills with a strong learning mindset

Good to Have

• Awareness of common agent patterns (ReAct, Human-in-the-Loop)
• Exposure to evaluation and tracing tools (LangSmith, Langfuse, Ragas, DeepEval)
• Basic Docker and exposure to AWS, Azure, or GCP
• Quick prototyping with Streamlit or Gradio
• Basic ML, Deep Learning, or NLP knowledge (e.g., Precision, Recall, F1 Score)
• Experience with Hugging Face and open-source models
• Awareness of AI security risks (OWASP Top 10 for LLM Applications) and data privacy regulations (DPDP Act, GDPR)
• Responsible use of AI coding assistants (Claude Code, Cursor, GitHub Copilot)
• Open-source contributions

What We Look For

• Learning Ability: You pick up new tools and technologies quickly
• AI Enthusiasm: You actively experiment with AI models and frameworks
• Builder Mindset: You can explain how your projects work and where they fail
• Critical Thinking: You verify AI outputs and understand the code you write

What We Offer

• Real-world GenAI and Agentic AI projects for global clients
• Structured onboarding and mentorship
• Collaborative, learning-driven culture
• Competitive compensation and growth opportunities.