If you are a fresher who wants to start your career in Generative AI, LLMs, RAG and Agentic AI, this AI Engineer opportunity at UnibotAI could be a strong entry point. Unlike a typical fresher software role, the position specifically mentions hands-on AI application development, LLM APIs, vector databases, AI agents, prompt engineering and RAG pipelines.
๐ข About UnibotAI
UnibotAI Official Website is an AI-driven platform focused on academic and employee career progression. Its public company profile describes UnibotAI as an AI-human driven platform working around areas such as jobs, careers, AI, voice bots, chatbots and interviews. The company is headquartered in Bengaluru and its current public profile lists software development as its industry.
UnibotAI is also actively working around Generative AI and Agentic AI. Its platform covers AI fundamentals, Machine Learning, NLP, Generative AI, prompt engineering and Agentic AI, while its recent hiring activity includes Agentic AI Engineer positions involving LangGraph, LangChain, CrewAI, RAG, LLMs, Python, APIs and AWS.
๐ Job Details
๐น Position: AI Engineer โ Fresher
๐น Experience: 0โ1 Years / Freshers
๐น Location: Bengaluru, Karnataka
๐น Employment: Full-Time
๐น Education: B.Tech/B.E./M.Tech/MCA/MSc in CS, AI/ML, Data Science or related fields
๐น Joining: Freshers and candidates with relevant projects/internships encouraged
๐น Application Email: support@unibotai.com
๐ Why Is This Role Good for Your Experience?
For a fresher, the biggest advantage is the breadth of modern AI technologies mentioned in the JD. You won’t be restricted to studying ML algorithms theoretically. The responsibilities cover building AI applications with Python, integrating models through APIs, creating RAG pipelines, working with embeddings and vector databases, testing AI agents and experimenting with prompt engineering.
This can help you build experience across the complete GenAI application lifecycle: user/problem โ data/context โ embeddings โ retrieval โ LLM โ agent/workflow โ API โ application โ evaluation.
The role can also provide a foundation for future positions such as AI Engineer, Generative AI Engineer, LLM Engineer, RAG Engineer, AI Application Developer or Agentic AI Engineer.
๐ ๏ธ Skills Required
๐น Strong Python programming
๐น AI and Machine Learning fundamentals
๐น LLM and Generative AI concepts
๐น RAG and retrieval workflows
๐น Embeddings and vector databases
๐น Prompt engineering and model evaluation
๐น AI agents and multi-agent concepts
๐น REST APIs, JSON and API integration
๐น Git/GitHub
๐น LangChain, LangGraph or LlamaIndex
๐น OpenAI/Gemini/Claude API exposure
๐น Analytical thinking and debugging
๐น Docker/cloud fundamentals as an advantage
๐น Good communication and willingness to learn
๐ฏ Expected UnibotAI Interview Rounds
Round 1 โ HR/Recruiter Screening: Expect questions about your education, AI interest, projects, availability, Bengaluru location and why you want to start your career in Generative AI.
Round 2 โ Python & AI Technical Round: Prepare Python programming, OOP, data structures basics, ML fundamentals, APIs, JSON and Git. Be ready to explain every AI project listed on your resume.
Round 3 โ GenAI/Project Discussion: This should be particularly important for this JD. Expect discussion around your RAG pipeline, embeddings, vector database, prompts, LLM API integration and AI-agent projects. UnibotAI’s recent public hiring activity strongly emphasizes Python, RAG, LangGraph/LangChain, LLM integrations, APIs and Agentic AI.
Round 4 โ Practical/Technical Evaluation: You may be asked to build or troubleshoot a small Python/AI workflowโfor example, an API-based chatbot, simple RAG application or prompt-evaluation exercise.
Round 5 โ Final/Founder or Team Discussion: Given the company’s relatively small public team profile, be prepared for a direct conversation around learning ability, ownership, communication and your ability to work in a fast-moving environment.
๐ฐ Salary Range
There is no official salary range published for this specific AI Engineer โ Fresher opening. Current Bengaluru market references vary substantially by employer and skill level. Recent data places entry-level AI Engineer compensation around โน5โ8 LPA in some Bengaluru openings, while broader 2026 market estimates can be higher for strong GenAI portfolios. (Pagaar India)
For this particular fresher role, a practical expectation would be approximately โน4โ8 LPA, depending on technical skills, project quality and interview performance. Treat this as a market estimate, not an official UnibotAI compensation figure.
๐ฅPreparation Tips
๐ก Build one complete RAG project: Don’t create five basic chatbot projects. Build one strong project using Python + embeddings + a vector database + RAG + an LLM API and explain its architecture clearly.
๐ก Understand retrieval, not just LangChain: Know why chunking, embeddings, similarity search, top-k retrieval and context injection are required.
๐ก Create an AI-agent mini project: Build an agent that can call two toolsโfor example, retrieve information and perform a calculation/API call. Be ready to explain the workflow.
๐ก Practice model evaluation: Prepare examples of hallucination, irrelevant responses, poor retrieval and prompt failures and explain how you would measure and improve them.
๐ก Know your APIs: Practice connecting an LLM API from Python, handling JSON responses, authentication, errors, timeouts and basic retry logic.
๐ก Prepare a GitHub demonstration: Keep your best AI project clean, documented and runnable. A README showing architecture, setup, sample inputs/outputs and limitations can make a fresher stand out.
๐ Unique Resume Tips
Your resume should immediately communicate โFresher + Python + Generative AI + Hands-on Projects.โ Don’t dedicate most of the page to generic coursework.
Put AI/GenAI Projects above unrelated projects. For every project, mention the technology and what you actually built: Python, RAG, embeddings, FAISS/ChromaDB, LLM API, LangChain, REST API, prompt engineering, etc.
Instead of writing โCreated an AI chatbot,โ write something measurable such as: โBuilt a Python-based RAG chatbot that retrieves relevant document chunks and generates grounded responses through an LLM API.โ
Add your GitHub link and ensure repositories contain meaningful code rather than only notebooks. Certifications can support your profile, but for this JD, a working AI project is more valuable than a long certification list.
๐ฉ How to Apply
Send your updated resume to support@unibotai.com.
๐ Subject: AI Engineer โ Fresher โ Bengaluru
๐ Mention your graduation year, relevant AI/ML experience, GitHub/portfolio link and availability in the email.
Freshers with strong RAG, chatbot, AI-agent, LLM or Generative AI projects are specifically encouraged to apply.
๐ Final Takeaway
This UnibotAI opportunity is particularly suited to fresh graduates who don’t want to wait for years before entering the Generative AI and Agentic AI ecosystem. If you can demonstrate strong Python fundamentals and one or two genuinely hands-on AI projects, you can potentially differentiate yourself from candidates who only have theoretical AI knowledge.
