Infra AI Automation Programmer

Infra AI Automation Programmers

• At least 2+ years of programming experience in Python • Handson experience in working on Gen AI • Handson experience in Tensorflow, Pytorch, Langchain and Prompt Engineering • Experience with vector databases and retrieval-augmented generation (RAG). • Familiarity with MLOps principles and tools for deploying and managing Gen AI models. • Understanding of ethical considerations and responsible AI frameworks. • Understanding of data structures, data modelling , SQL & NOSQL • Object oriented and functional programming & GIT • Knowledge of basic algorithms and object-oriented and functional design principles • Deep Knowledge of Mathematics, Probability, Statistics, and Algorithms • Good Communication skills • Good analytical and problem-solving skills •Besides the professional qualifications of the candidates, we place great importance in addition to various forms personality profile. These include: • High analytical skills • A high degree of initiative and flexibility • High customer orientation • High quality awareness • Excellent verbal and written communication skills As an Infra AI Automation Programmer you will work on design, development, and deployment of AI systems that generate content or data, often using techniques such as deep learning, neural networks, and generative models using Python backend coding. • Meet with clients in and remotely to understand their business objectives, challenges, and identify potential use cases for Generative AI. • Assess the client's existing technology infrastructure, data landscape, and AI maturity to determine the feasibility and best approaches for Gen AI adoption. • Conduct workshops and discovery sessions to brainstorm Gen AI applications across various business functions (e.g., content creation, customer service, product development, marketing). Gen AI Strategy and Solution Design: • Develop tailored Gen AI strategies and roadmaps for clients in outlining specific use cases, implementation plans, and expected business outcomes. • Design Gen AI solutions architecture, considering factors such as model selection (e.g., large language models (LLMs), diffusion models), data requirements, integration with existing systems, and scalability. • Evaluate and recommend appropriate Gen AI platforms, tools, and APIs (e.g., OpenAI, Google AI, Azure AI, open-source libraries) relevant to the client's needs and the Indian market. • Advise on prompt engineering techniques to optimize the output and performance of Gen AI models for specific client applications.