๐ข Company Introduction
InspironLabs Software Systems Pvt Ltd is hiring enthusiastic professionals for the position of AI Engineer โ Generative AI & Agentic AI in Bangalore. The opportunity is focused on emerging artificial intelligence technologies, including Large Language Models (LLMs), Generative AI, Agentic AI, and Python backend development.
The company is looking for candidates interested in developing intelligent applications and solving real-world business problems using modern AI technologies. This position is particularly relevant for candidates who want to build their careers in the rapidly evolving Generative AI ecosystem.
For fresh graduates and early-career professionals, this hiring opportunity offers a chance to apply their AI/ML knowledge to practical engineering challenges.
๐ Job Overview
- ๐ข Company: InspironLabs Software Systems Pvt Ltd
- ๐ผ Job Title: AI Engineer โ Generative AI & Agentic AI
- ๐ Location: Bangalore, Karnataka
- ๐ข Work Mode: Work From Office (WFO)
- ๐ฏ Experience: 0โ2 Years
- ๐ Qualification: Not specifically disclosed
- ๐จโ๐ป Eligible Candidates: Freshers and experienced candidates
- ๐ Freshers Eligibility: Candidates with relevant AI/ML training, certifications, internships, or hands-on projects are welcome.
- ๐ ๏ธ Key Technologies: Python, FastAPI, Flask, Generative AI, LLMs, RAG, LangChain, LangGraph, LlamaIndex, CrewAI, and Vector Databases.
- ๐ Employment Type: Not specified in the announcement.
- ๐ฐ Salary: Not disclosed.
- ๐ฉ Application Mode: Email your updated resume to the recruiter.
Candidates with practical knowledge of AI application development and Python backend engineering are encouraged to apply.
๐ ๏ธ Key Responsibilities
Based on the advertised technical requirements, candidates should be prepared for responsibilities involving the following areas:
- ๐ค Generative AI Development: Build intelligent applications using Generative AI technologies and Large Language Models.
- ๐ Python Backend Development: Develop backend components using Python and frameworks such as FastAPI or Flask.
- ๐ API Integration: Create and integrate REST APIs to connect AI applications with external services and databases.
- ๐ RAG Implementation: Work with Retrieval-Augmented Generation pipelines to improve the relevance of LLM responses.
- ๐ง Vector Search: Understand embeddings, semantic search, and vector databases for retrieving relevant information.
- โ๏ธ Agentic AI: Explore AI agents, tool calling, and orchestration to develop applications capable of executing multi-step tasks.
- ๐ AI Evaluation: Understand methods for evaluating AI-generated responses, application performance, and reliability.
- ๐ AI Security: Consider security risks and responsible practices when developing AI-powered applications.
These points reflect the technologies and expectations in the announcement, rather than a confirmed internal responsibility list.
๐ Why Is This Role a Good Opportunity?
This opportunity is particularly attractive for candidates interested in building a career in Generative AI and Agentic AI.
- ๐ Emerging Technologies: Gain exposure to LLMs, AI agents, RAG pipelines, and modern AI frameworks.
- ๐จโ๐ป Practical Engineering: Apply Python programming and backend development knowledge to AI-powered applications.
- ๐ง Specialized Learning: Develop an understanding of embeddings, vector databases, prompt engineering, and model fine-tuning.
- ๐ Fresher-Friendly Eligibility: Candidates with relevant training, certifications, internships, or personal projects can apply.
- ๐ Career Development: Build technical foundations relevant to AI Engineer, Generative AI Developer, and LLM Application Developer career paths.
For candidates with 0โ2 years of experience, this role aligns well with the growing demand for engineers who can combine software development with practical AI knowledge.
๐ง Skills Required
Candidates should focus on developing the following technical skills:
๐ Programming and Backend Development
- Strong understanding of Python programming.
- Knowledge of FastAPI or Flask.
- Understanding of REST API development and integration.
- Familiarity with databases and backend architecture.
๐ค Generative AI and LLMs
- Understanding of Large Language Models and Generative AI.
- Prompt engineering techniques and structured prompting.
- Knowledge of model fine-tuning concepts.
๐ RAG and Vector Databases
- Understanding of Retrieval-Augmented Generation.
- Knowledge of embeddings and semantic search.
- Familiarity with vector databases and document retrieval.
โ๏ธ Agentic AI Frameworks
- Understanding of AI agents and tool orchestration.
- Exposure to LangChain, LangGraph, LlamaIndex, or CrewAI.
- Awareness of MCP and AI application integration.
๐ Additional Knowledge
- Machine Learning and Deep Learning fundamentals.
- AI evaluation and observability.
- AI security and responsible AI practices.
๐ค Expected Interview Rounds
The exact InspironLabs interview process has not been disclosed. However, candidates can prepare for these indicative stages:
- ๐ HR Screening: Discussion about educational background, experience, availability, Bangalore WFO preference, and interest in AI engineering.
- ๐ Python Technical Interview: Questions on Python fundamentals, OOP, data structures, exception handling, APIs, and backend development.
- ๐ค Generative AI Technical Round: Questions on LLMs, tokens, embeddings, prompt engineering, hallucinations, and model fine-tuning.
- ๐ Practical AI Assessment: Possible exercises involving a basic RAG pipeline, document retrieval, API integration, or vector database.
- โ๏ธ Project Discussion: Explanation of personal AI projects, frameworks used, architecture, challenges, and individual contributions.
- ๐ฅ Managerial Discussion: Potential discussion about problem-solving, communication, learning ability, and role expectations.
These are preparation suggestions, not company-confirmed interview rounds.
๐ฐ Expected Salary Range
The company has not disclosed the compensation package for this position.
For candidates with 0โ2 years of experience in Bangalore, compensation can vary considerably depending on Python proficiency, practical AI project experience, technical interview performance, and the employer’s salary structure.
Rather than assuming an unsupported salary figure, candidates should confirm the offered CTC, fixed pay, variable components, and benefits directly with the recruiter during the hiring process.
๐ Preparation Tips for This Specific Job
To prepare effectively for the InspironLabs AI Engineer position, concentrate on practical implementation:
- ๐ Practice Python: Revise OOP, dictionaries, lists, functions, decorators, exception handling, and asynchronous programming.
- ๐ Build REST APIs: Create a small FastAPI application with endpoints for submitting questions and returning AI-generated responses.
- ๐ค Understand LLMs: Study tokens, context windows, temperature, hallucinations, and prompt engineering.
- ๐ Implement RAG: Build a document-question-answering application using document chunking, embeddings, retrieval, and an LLM.
- ๐๏ธ Explore Vector Databases: Understand similarity search, indexing, metadata filtering, and vector storage.
- โ๏ธ Learn Agentic AI: Build a simple AI agent that selects tools and performs multiple steps to complete a task.
- ๐งฉ Explore Frameworks: Practice at least one framework, such as LangChain or LangGraph, and understand its architecture.
- ๐ Study AI Security: Learn about prompt injection, sensitive data exposure, and secure tool execution.
A strong portfolio project combining Python, FastAPI, RAG, and an LLM can help demonstrate practical knowledge during interviews.
๐ Resume Tips
Freshers and experienced candidates should tailor their resumes to the advertised AI engineering requirements.
- ๐ Highlight Technical Skills: Include Python, FastAPI, Flask, REST APIs, Generative AI, LLMs, RAG, and relevant frameworks where applicable.
- ๐ Showcase AI Projects: Include document-based chatbots, RAG applications, AI assistants, or agentic workflows.
- ๐ Explain Project Contributions: Mention your individual responsibilities, technologies used, implementation approach, and measurable results where available.
- ๐ Mention Relevant Training: Include AI/ML certifications, internships, workshops, and practical training.
- ๐ง Include Relevant Keywords: Use terms such as Prompt Engineering, Embeddings, Vector Databases, LangChain, LangGraph, and MCP when supported by your actual experience.
- ๐ Keep Formatting ATS-Friendly: Use clear headings, readable fonts, and concise project descriptions.
Avoid listing frameworks or technologies that you cannot explain confidently during an interview.
๐ฉ How to Apply
Interested candidates can apply directly by sharing their updated resumes through the recruiter email provided in the hiring announcement.
- ๐ง Recruiter Email: Sheetal.k@inspironlabs.com
- ๐ข Company: InspironLabs Software Systems Pvt Ltd
- ๐ผ Position: AI Engineer โ Generative AI & Agentic AI
- ๐ Job Location: Bangalore
- ๐ฏ Experience: 0โ2 Years
Suggested Email Subject: Application for AI Engineer โ Generative AI & Agentic AI
Mention your relevant Python skills, AI/ML training, certifications, internships, and project experience in your application email.
๐ Final Thoughts
The AI Engineer โ Generative AI & Agentic AI opportunity at InspironLabs is worth exploring for freshers and early-career professionals who want to enter the AI engineering field.
Candidates with strong Python fundamentals, practical Generative AI knowledge, RAG implementation experience, and an understanding of AI agents should consider applying.
If you have developed AI projects during your academic journey or through personal learning, showcase them confidently in your resume.
๐ Prepare well, highlight your practical skills, and take the next step towards building your career in Artificial Intelligence!
