
Generative AI Engineer
4 weeks ago
Hybrid from Noida Office
Job Responsibility
In this role, we are seeking a highly skilled and experienced AI Engineer with hands-on expertise in
Generative AI, AWS Bedrock, Azure Open AI, Document Intelligence tools, Huggingface, Agentic AI, and
Advanced Data Pipelines. It's platforms semantic kernel, autogen, langchain.
Responsibilities
● Architect and implement advanced generative AI models, focusing on applications such as image
and text generation, image and document extraction, RAG, Prompt engineering, and synthetic
data generation.
● Advanced Prompt Engineering techniques. Stay at the forefront of AI/ML and generative AI
advancements, driving the adoption of new technologies and best practices within the team.
● Develop, fine-tune, and optimize generative AI models, ensuring they meet performance,
scalability, and business objectives. Firm grasp on tools to compare outputs of each model and
compare against each other.
● Apply solid data science principles to enhance AI/ML models, using statistical analysis and
machine learning techniques to improve model accuracy and efficiency.
● Work closely with data engineers, software developers, and product managers to integrate
generative AI models into products and services, aligning with business objectives.
● Ensure that AI models are designed and deployed with ethical considerations, adhering to
industry standards and regulatory requirements.
Qualifications we seek in you
Minimum Qualifications / Skills
● Bachelor’s or Master’s degree in computer science, AI, Machine Learning, Data Science, or a
related field, with 5+ years of experience in AI/ML, particularly with generative AI models.
● Strong expertise in developing and deploying generative AI models. Proficiency in Python and
experience with AI development libraries such as TensorFlow and PyTorch. Experience with
Azure OpenAI, Open Source LLMs, and LangChain.
● Solid experience in applying data science principles, including statistical analysis, data
preprocessing, and machine learning, to enhance AI/ML models.
Preferred Qualifications/ Skills
● Familiarity with advanced techniques such as Retrieval-Augmented Generation (RAG),
fine-tuning, prompt engineering, and zero-shot learning.
● Familiarity with NLP or computer vision related to generative AI applications.
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