Generative AI & Agentic AI Engineer

Job Title:

Experience:

Generative AI & Agentic AI Engineer

Key Responsibilities

• Design and propose solution architectures for

  Generative AI (LLMs)

  , advanced Conversational AI chatbots, and cloud AIaaS platforms.
• Develop and implement applications using advanced Generative AI models such as

  OpenAI GPT, Anthropic Claude, Meta Llama2, and Google Gemini

  .
• Train, fine-tune, and deploy large language models for domain-specific tasks using techniques like

  instruction tuning, RLHF, and parameter-efficient fine-tuning (LoRA, adapters, etc.)

  .
• Architect solutions incorporating

  Retrieval-Augmented Generation (RAG), Transformer architectures, LangChain, SQLChain

  , ensuring optimal model performance and scalability.
• Hands-on development with

  RAG systems, LLM fine-tuning, and vector databases

  .
• Benchmark and measure performance of various LLMs and AI applications.
  
• Drive end-to-end implementation and deployment using

  Azure and AWS services

  .
• Stay updated on emerging trends, AI patterns, and innovations to continuously enhance solution design and deployment processes.
  

Required Qualifications & Skills

• Bachelor’s, Master’s, or PhD in

  Computer Science, Electrical Engineering, Artificial Intelligence

  , or equivalent experience.
• Strong

  Python programming skills

  and fundamentals of software design and optimization.
• In-depth knowledge of

  ML/DL techniques and algorithms

  , with hands-on exposure to

  CNNs, RNNs (LSTM), Transformers (BERT, BART, GPT/T5, Megatron, LLMs)

  .
• Experience with

  Conversational AI technologies

  : NLU, NLG, dialogue systems, information retrieval, QA systems, and machine translation.
• Proven experience training

  BERT, GPT, and Megatron models

  for NLP/dialog tasks using

  PyTorch

  , including data wrangling and tokenization.
• Familiarity with

  MLOps lifecycle

  , dataset versioning, and database management (

  SQL, MongoDB

  ).
• Experience with

  end-to-end MLOps platforms

  : Kubeflow, MLFlow, Airflow.
• Strong

  collaboration, communication, and influencing skills

  within dynamic, cross-functional teams.

Preferred Attributes

• Hands-on experience with

  cloud-based AI deployments

  , including

  Azure/AWS AI services

  .
• Ability to translate complex AI models into business-ready solutions.
  
• Passion for staying at the forefront of AI research and innovation.