Infra AI Automation Programmers

• You will need at least 2+ years of programming experience in Python.
  
• You must have hands-on experience working on Generative AI (Gen AI).
  
• Proficiency is required with Tensorflow, Pytorch, Langchain, and Prompt Engineering.
  
• Experience with vector databases and retrieval-augmented generation (RAG) is essential.
  
• Familiarity with MLOps principles and tools for deploying and managing Gen AI models.
  
• Understanding of ethical considerations and responsible AI frameworks.
  
• Knowledge of data structures, data modeling, SQL & NOSQL.
  
• Proficiency in object-oriented and functional programming along with GIT version control.
  
• Solid knowledge of basic algorithms and design principles (object-oriented and functional).
  
• Deep understanding of Mathematics, Probability, Statistics, and Algorithms.
  
• Strong communication skills and the ability to analyze complex problems.

Client Engagement and Needs Analysis:

• Meet with clients in-person or remotely to understand their business objectives and identify potential use cases for Generative AI.
  
• Assess existing technology infrastructure, data landscape, and AI maturity levels.
  
• Conduct workshops to brainstorm Gen AI applications across various business functions such as content creation, customer service, product development, and marketing.

Gen AI Strategy and Solution Design:

• Develop tailored Gen AI strategies and roadmaps for clients, outlining specific use cases and implementation plans.
  
• Design Gen AI solutions architecture considering model selection (LLMs, diffusion models), data requirements, system integration, and scalability.
  
• Evaluate and recommend appropriate Gen AI platforms, tools, and APIs relevant to the Indian market.
  
• Advise on prompt engineering techniques to optimize output and performance.

Technical Guidance and Implementation Support:

• Provide technical expertise and guidance to client development teams and internal engineers on implementing Gen AI solutions.
  
• Assist with data preparation, cleaning, and feature engineering for model training and fine-tuning.
  
• Collaborate with data scientists and ML engineers to fine-tune pre-trained models using client-specific data.
  

Ethical Considerations and Responsible AI:

• Educate clients on ethical implications including bias, fairness, transparency, and potential misuse.
  
• Advise on responsible AI practices for compliant deployment.
  
• Help develop guidelines and policies for the responsible use of Gen AI within organizations.