We are seeking a Generative AI Engineer with 3.5+ years of experience to work with cutting-edge AI technologies, including RAG (Retrieval-Augmented Generation), Agentic AI, and transformer-based architectures, along with strong Python programming skills, to design, implement, and optimize AI-driven data solutions.

AI Powered Tech Talent

Roles & Responsibilities:

Design and implement AI-powered data pipelines leveraging RAG models and transformers for

advanced knowledge retrieval and generation tasks.

Utilize LangChain, LangGraph, and other frameworks to build and integrate intelligent workflows and conversational agents.

Develop Agentic AI solutions to create autonomous, goal-driven agents that interact with dynamic environments and data.

Optimize data storage, processing, and retrieval techniques for large-scale AI platforms.

Engineer prompt structures for optimized performance in generative AI tasks, including natural language processing (NLP) and multimodal applications.

Ensure robust data privacy and security measures are in place for all AI-driven systems.

Continuously monitor, troubleshoot, and enhance AI system performance.

Collaborate with cross-functional teams (e.g., Data Scientists, Engineers) to integrate generative AI models into real-world data solutions.

Required Technical Skills:

3.5+ years of hands-on experience in Python for building AI models and systems.

Strong expertise in Generative AI frameworks, such as RAG (Retrieval-Augmented Generation),

transformers, and agentic models.

Proficiency in LangChain, LangGraph, and Agentic AI frameworks to develop intelligent,

goal-oriented agents and workflows.

Hands-on experience with prompt engineering for optimizing generative AI outputs.

Strong experience with cloud-based platforms like AWS, Azure, or GCP for deploying AI solutions.

Deep understanding of data governance, compliance, and security standards in AI applications.

Familiarity with NLP libraries (like Hugging Face, spaCy, NLTK) and machine learning

frameworks (like TensorFlow, PyTorch).

Experience working with Databricks or similar platforms for AI/ML model deployment and scaling.

Preferred Skills:

Experience in deploying AI models with real-time inference capabilities.

Familiarity with reinforcement learning, active learning, and multi-agent systems.

Knowledge of computer vision and multimodal AI techniques (text, images, video, etc.).

Understanding of data modeling for AI-powered systems and integration with existing data

pipelines.

Educational Qualification:

- 15 years full time education is required.

Data Platform Engineer