Generative AI Engineer
AS Technology Corporation
Job Description
Position: Python + Generative AI Engineer Experience: 6–10 Years Location: Hyderabad / Bangalore Open Positions: 6 Job Summary We are seeking an experienced Python + Generative AI Engineer to design, develop, and deploy enterprise-grade AI solutions. The ideal candidate will have a strong foundation in Python development, software engineering best practices, and hands-on experience with Generative AI technologies, including prompt engineering, Retrieval-Augmented Generation (RAG), model fine-tuning, and enterprise LLM integrations. Key Responsibilities Design, develop, and maintain scalable AI-powered applications using Python.
Build and optimize Generative AI solutions for enterprise use cases. Develop and refine prompts to improve LLM performance and response quality. Design and implement Retrieval-Augmented Generation (RAG) pipelines.
Fine-tune, evaluate, and optimize large language models for domain-specific applications. Integrate enterprise data sources securely with LLM-based applications. Develop REST APIs and backend services to support AI solutions.
Write clean, reusable, and well-tested code following software engineering best practices. Collaborate with cross-functional teams to deliver high-quality AI products. Required Skills Programming & Software Engineering Strong proficiency in Python.
Hands-on experience with NumPy , Pandas , and Scikit-learn . Strong understanding of Object-Oriented Programming (OOP). Experience developing REST APIs.
Knowledge of software testing and debugging methodologies. Familiarity with software engineering best practices. Generative AI Hands-on experience with: Prompt Engineering and Prompt Optimization Retrieval-Augmented Generation (RAG) LLM Fine-tuning Model Evaluation and Performance Optimization Experience integrating enterprise data securely with Large Language Models (LLMs).
Understanding of AI governance, security, and responsible AI practices. Preferred Qualifications Experience with LangChain, LlamaIndex, or similar LLM orchestration frameworks. Knowledge of vector databases and embeddings.
Experience working with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with MLOps or AI deployment pipelines.