Generative Ai Engineer

Description:

The ideal candidate will be a proficient expert in Generative AI and Large Language Models (LLMs) with a proven track record of designing and deploying end-to-end automation solutions. You will be responsible for leading the research and development of cutting-edge AI applications, designing robust application architecture, and driving automation in IT Operations (ITOps). This role requires deep technical expertise in AI frameworks, vector databases, and Python programming, combined with strong leadership and communication skills.

𝗞𝗲𝘆 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀:

• Design and implement application architecture for Generative AI use cases, reducing ideation-to-implementation time significantly.

• Lead the development of advanced AI platforms capable of automating full-stack software creation from simple prompts , incorporating features like self-healing and auto-generated tested code.

• Develop and deploy sophisticated knowledge bots and conversational AI using historical data and SOPs to dramatically reduce resolution times for L2 support.

• Create chatbots for ITOps automation that generate deployment scripts for Ansible and Terraform based on existing SOPs.

• Pioneer the creation of dynamic, multi-agent AI frameworks using Langchain to provide innovative solutions for customer use cases.

• Orchestrate and deploy a variety of machine learning models, including TensorFlow, CNN, and SciPy, to automate ITSM workflows.

• Lead Generative AI development projects across multiple client engagements and train and mentor other associates in the field.

• Drive innovation within the company, including contributing to patentable inventions in AI product development.

𝗥𝗲𝗾𝘂𝗶𝗿𝗲𝗱 𝗤𝘂𝗮𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀 & 𝗦𝗸𝗶𝗹𝗹𝘀:

• Experience: 6+ years of professional experience in software development and AI.

• Education: Bachelor of Technology in Electronics and Communications Engineering or a related field.

• Generative AI Platforms: Hands-on experience with Azure Open AI, Google Cloud Platform (GCP), Groq, and HuggingFace.

• Large Language Models (LLMs): Deep proficiency with models such as GPT-4o, GPT-4, Llama 3.2/3.1, Google Gemini (Pro, Flash), and Mistral/Mixtral.

• AI Frameworks: Expertise in Langchain, Autogen, and Crew AI.

• Vector Databases: Skilled in using vector databases like PGVector, ChromaDB or the likes.

• Databases: SQL server or PostgreSQL experience.

• Programming: Expert-level in at-least one of ( Python, Java, Node JS) and React programming skills.

• DevOps & MLOps: Experience with Azure DevOps, automated testing, and MLOps practices.

• Machine Learning: Proficient in developing, deploying, and optimizing TensorFlow models.