Generative AI Engineer

InvoLead; Gurugram District; On-site; INR 1,200,000 - 2,500,000; Full time

Job summary

InvoLead seeks a proficient ML Engineer to design, develop, and deploy multi-agent GenAI systems at scale. You will implement Agentic AI architectures with LangGraph and LangChain, leveraging LLMs and RAG architectures across cloud platforms.

Ideal candidates have 2-5 years in ML, strong Python skills, and hands-on experience with TensorFlow/PyTorch, OpenAI APIs, and vector databases. You will stay ahead with the latest advancements and contribute to production-ready AI solutions.

Qualifications

• B Tech/M Tech in Computer/IT or related field from reputed engineering colleges.
• 2-5 years of hands-on experience in ML domain.
• Practical experience with Generative AI & LLMs, Agentic AI and multi-agent systems, LangGraph, LangChain, Hugging Face, OpenAI APIs, RAG architecture and vector databases.

Responsibilities

• Design, develop, and implement state-of-the-art generative models for applications like text generation, image synthesis and content creation.
• Implement Agentic AI architectures using LangGraph, LangChain, and custom orchestration logic.
• Work with open source LLMs like Llama, Falcon, BERT, Mistral, RAG systems, and perform prompt engineering.
• Pre-process and analyze large datasets to extract meaningful features for training generative models.
• Optimize and fine-tune generative models for efficiency and performance.
• Deploy and manage AI solutions on cloud platforms (AWS / Azure).
• Implement strategies to reduce model latency and resource consumption.
• Develop evaluation metrics to assess model performance and quality.
• Architect scalable production systems and document code and methodologies.
• Stay updated with GANs, VAEs, and related generative AI techniques.
• Contribute to IP by researching novel approaches to business challenges.

Skills

Generative AI

Python

LLMs

TensorFlow

PyTorch

OpenAI APIs

RAG architecture

Vector databases

AWS

Azure

Education

B Tech / M Tech in Computer/IT

Tools

LangGraph

LangChain

Hugging Face

OpenAI APIs

Vector databases

Job description

This role involves working on real-world business problems by designing, developing, and deploying multi agent GenAI systems that operate concurrently to solve complex tasks at scale.

Duties and Responsibilities:

• Design, develop, and implement state-of-the-art generative models for various applications, such as text generation, image synthesis and content creation.
• Implement Agentic AI architectures using frameworks such as LangGraph, LangChain, and custom orchestration logic.
• Experience working on open source LLMs like Llama, Falcon, BERT, Mistral etc., RAG systems and prompt engineering
• Pre-process and analyze large datasets to extract meaningful features and patterns suitable for training generative models.
• Optimize and fine-tune generative models for efficiency, scalability, and improved performance.
• Deploy and manage AI solutions on cloud platforms (AWS / Azure), following best practices.
• Implement strategies for reducing model latency and resource consumption.
• Develop and implement robust evaluation metrics to assess the performance and quality of generative models.
• Architecture design and building scalable production systems
• Document code, models, and methodologies thoroughly to facilitate knowledge sharing and future development.
• Stay updated with the latest advancements in generative models, including GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other relevant techniques.
• Stay at the forefront of the latest research papers and publications in the field of generative AI.
• Contribute to the company's intellectual property by researching and developing novel approaches to address specific business challenges.

Requirements:

• B Tech/M Tech in Computer/IT or related field from reputed engineering colleges
• 2-5 years of hands-on experience in ML domain.
• Practical experience with Generative AI & LLMs, Agentic AI and multi-agent systems, LangGraph, LangChain, Hugging Face, OpenAI APIs, RAG architecture and vector databases.
• Proven experience in developing generative models, with expertise in deep learning frameworks such as TensorFlow or PyTorch.
• Strong programming skills in languages like Python and proficiency in machine learning libraries.
• Solid understanding of neural network architectures, optimization techniques, and training methodologies
• Work experience on cloud platforms like AWS/Azure is desired.