AI Generative Engineer

Job Title: AI / Generative AI Engineer

Department: Artificial Intelligence / Machine Learning / Software Development

Experience: 0–1 Year (Freshers Can Apply)

Employment Type: Full-Time

Job Location: Bangalore, Karnataka

Qualification: B.E. / B.Tech / BCA / MCA / M.Tech / M.Sc. in Computer Science, AI, Data Science, or Related Disciplines

Job Summary

We are looking for a passionate, innovative, and technically motivated AI / Generative AI Engineer (Fresher) to join our Artificial Intelligence and Machine Learning team in Bangalore.

The candidate will be responsible for assisting in the development, testing, and deployment of AI-powered applications using Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLMs), and Generative AI technologies.

The ideal candidate should have strong Python programming fundamentals, basic knowledge of machine learning, and an understanding of Generative AI concepts such as prompt engineering, Retrieval-Augmented Generation (RAG), embeddings, and LLM integration.

Key Responsibilities

1. AI & Machine Learning Development

• Assist in designing, developing, and testing AI and machine learning models.
• Support data preprocessing, feature engineering, and model evaluation.
• Implement basic machine learning algorithms using Python.
• Work with structured and unstructured datasets.
• Collaborate with senior engineers to improve model accuracy and performance.

2. Generative AI & LLM Applications

• Assist in developing applications using Large Language Models such as GPT, Gemini, Llama, or other available models.
• Integrate LLM APIs into software applications.
• Develop and optimize prompts for different business use cases.
• Support the development of AI chatbots, virtual assistants, and content generation systems.
• Evaluate AI-generated responses for accuracy, relevance, and consistency.
• Assist in identifying and reducing hallucinations and unreliable model outputs.

3. Retrieval-Augmented Generation (RAG)

• Support the development of RAG-based applications.
• Work with document processing, text chunking, and embeddings.
• Assist in integrating vector databases such as FAISS, Chroma, or Pinecone.
• Implement basic semantic search and information retrieval workflows.
• Test and evaluate retrieval quality and response accuracy.

4. Natural Language Processing (NLP)

• Assist in developing NLP applications for text classification, summarization, and information extraction.
• Perform text preprocessing, tokenization, and data cleaning.
• Work with NLP libraries such as NLTK, spaCy, or Hugging Face Transformers.
• Support experimentation with pretrained language models.
• Analyze and improve NLP application performance.

5. AI Application Development & API Integration

• Develop Python-based backend components for AI applications.
• Assist in building REST APIs using FastAPI or Flask.
• Integrate AI models with web applications and databases.
• Write clean, reusable, and maintainable code.
• Support debugging, testing, and performance optimization.

6. Model Testing & Evaluation

• Test AI models and applications using predefined evaluation metrics.
• Analyze model outputs and identify errors or inconsistencies.
• Assist in preparing test datasets and evaluation reports.
• Monitor basic model performance, response time, and reliability.
• Support responsible AI practices, including data privacy, fairness, and secure handling of information.

7. Collaboration & Documentation

• Work closely with AI engineers, data scientists, and software developers.
• Participate in technical discussions, code reviews, and project meetings.
• Maintain technical documentation for AI workflows and applications.
• Use Git and GitHub for version control.
• Stay updated with advancements in Generative AI and machine learning technologies.

Required Technical Skills

1. Programming

• Good knowledge of Python programming.
• Understanding of object-oriented programming concepts.
• Familiarity with data structures and algorithms.
• Basic knowledge of SQL and database operations.
• Experience using Jupyter Notebook or Google Colab.

2. Machine Learning Fundamentals

• Understanding of supervised and unsupervised learning.
• Knowledge of regression, classification, and clustering.
• Familiarity with model training, validation, and testing.
• Basic understanding of overfitting, underfitting, and model evaluation.
• Knowledge of NumPy, Pandas, and Scikit-learn.

3. Generative AI & Large Language Models

• Basic understanding of Generative AI and LLM concepts.
• Knowledge of prompt engineering techniques.
• Familiarity with tokens, embeddings, and context windows.
• Understanding of Retrieval-Augmented Generation (RAG).
• Awareness of fine-tuning and model inference.
• Basic knowledge of LLM APIs.

4. AI Frameworks & Libraries

• Familiarity with PyTorch or TensorFlow.
• Basic understanding of Hugging Face Transformers.
• Awareness of LangChain or LlamaIndex.
• Knowledge of NLP libraries such as NLTK or spaCy.

5. Databases & Vector Search

• Basic knowledge of SQL or MongoDB.
• Understanding of vector embeddings and similarity search.
• Familiarity with FAISS, Chroma, or other vector databases is an advantage.

6. Development Tools

• Git and GitHub.
• Visual Studio Code.
• Jupyter Notebook / Google Colab.
• Basic knowledge of REST APIs.
• Familiarity with FastAPI or Flask.
• Basic understanding of Docker and cloud computing.

Required Soft Skills

• Strong analytical and logical reasoning abilities.
• Excellent problem-solving skills.
• Curiosity and interest in emerging AI technologies.
• Good mathematical and statistical aptitude.
• Strong debugging and troubleshooting abilities.
• Effective verbal and written communication skills.
• Ability to work collaboratively in technical teams.
• Attention to detail and model accuracy.
• Willingness to learn new frameworks and technologies.
• Good time-management and organizational skills.

Educational Qualifications

• B.E. / B.Tech in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or Information Technology.
• BCA / MCA / M.Tech / M.Sc. in Computer Science, AI, or related disciplines.
• Fresh graduates from the 2025 and 2026 batches are encouraged to apply.
• Candidates with relevant AI certifications, internships, or academic projects will have an added advantage.

Preferred Qualifications

• Academic or personal projects involving Generative AI, LLMs, or machine learning.
• Experience building AI chatbots or question-answering applications.
• Familiarity with OpenAI-compatible APIs, Hugging Face, or other LLM platforms.
• Basic experience developing RAG-based applications.
• Understanding of prompt optimization and LLM evaluation.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Familiarity with AI model deployment and monitoring.
• Participation in AI hackathons, research projects, or open-source contributions.
• Awareness of AI security, prompt injection risks, and responsible AI principles.

Key Performance Indicators (KPIs)

• Quality and functionality of developed AI applications.
• Accuracy and relevance of AI-generated outputs.
• Timely completion of assigned development tasks.
• Code quality, readability, and maintainability.
• Effectiveness of model testing and evaluation.
• Successful integration of LLM APIs and AI components.
• Performance and reliability of AI workflows.
• Quality of technical documentation.
• Collaboration with engineering and data science teams.
• Continuous improvement in AI and GenAI technical skills.

Ideal Candidate

We are seeking a passionate, technically curious, and self-motivated fresher with a strong interest in Artificial Intelligence, Machine Learning, and Generative AI.

The candidate should demonstrate good Python programming skills, an understanding of machine learning fundamentals, and basic knowledge of LLMs, prompt engineering, and AI application development.

Practical exposure through academic projects, internships, hackathons, or personal AI applications will be considered an advantage.

A willingness to experiment, learn emerging technologies, and contribute to innovative AI-powered solutions is essential.