Generative AI Engineer

Role & responsibilities

• Develop and fine-tune LLMs using techniques like RAG, transfer learning, or domain-specific adaptation

• Build AI agents using frameworks like LangChain or CrewAI to manage dynamic and multi-step workflows

• Work with vector databases (e.g., Pinecone) to enable semantic search and retrieval

• Design and maintain ETL pipelines and ensure smooth data preprocessing and transformation

• Implement NLP solutions for tasks like intent detection, sentiment analysis, and content generation

• Develop backend APIs and services using Python frameworks like FastAPI or Flask

  Contribute to scalable microservice-based architectures

Requirements

• Bachelor's degree in Computer Science, Information Technology, or a related field.

• 2 to 6 years in AI/ML development and backend system

• Machine Learning Fundamentals: Strong grasp of algorithms, model training, evaluation, and tuning

• Generative AI Models: Experience working with LLMs, RAG architecture, and fine-tuning techniques

• LangChain or Similar Frameworks: Hands-on experience building AI workflows using toolkits like LangChain

• Natural Language Processing (NLP): Proficiency in text analytics, classification, tokenization, embeddings

• Vector Databases: Practical use of tools like Pinecone, FAISS, or similar for retrieval-augmented generation

• Big Data Handling: Ability to work with large datasets, optimize storage, and processing pipelines

• SQL/NoSQL: Experience in querying and managing structured and unstructured data

• Python & API Development: Proficiency in Python and frameworks like FastAPI or Flask

• ETL & Data Preprocessing: Strong understanding of building pipelines for clean and efficient data processing

• Soft Skills: Strong problem-solving, communication, and collaboration abilities

• Note: We are seeking for experience in Agentic AI.