GenAI- Python Lead

Reyika; Dadri, Delhi; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Reyika is seeking a Senior GenAI Engineer to build and deploy GenAI applications from scratch, leveraging frameworks like Autogen and Crew.ai. You will develop high-quality Python code, implement RAG architectures, and integrate with multi-modal LLMs.

The role requires experience with REST/SOAP, cloud platforms (Azure, AWS, GCP), and front-end tech like React and Streamlit. You will fine-tune SLMs for domain data, work on data modernization, and guide junior developers to uphold technical

Qualifications

• Deep expertise in Python for GenAI applications.
• Productionize GenAI apps beyond PoCs using scalable frameworks.
• LLM frameworks like Autogen and Crew.ai.
• Experience with large-scale structured and unstructured data.
• REST/SOAP API integration experience.
• Fine-tune SLM for domain-specific data.
• Prompt injection fallback and security tooling.
• Anti-hallucination tools and anti-gibberish techniques.
• Front-end knowledge: React, Streamlit, AG Grid, JavaScript.
• Cloud experience with Azure, AWS, and GCP.
• Advanced skills in RAG and Modular RAG.
• Data modernization and transformation expertise.

Responsibilities

• Application Development: Build GenAI applications from scratch.
• Python Programming for GenAI solutions.
• Implement Retrieval-Augmented Generation (RAG) architectures.
• Work on Multi-Modal LLM Applications.
• Fine-tune SLM for domain data and use cases.
• Deploy and manage GenAI apps on Azure, GCP, AWS.
• Design data pipelines to support GenAI apps.
• Front-end integration for seamless UI with GenAI backends.
• LLM fine-tuning and LLMOps implementation.
• Mentor junior developers and promote technical excellence.

Skills

Python

GenAI

Autogen

Crew.ai

LLM frameworks

RAG & Modular RAG

REST APIs

React/JavaScript/Streamlit

LLMOps / fine-tuning

Data handling / large-scale data

Tools

Autogen

Crew.ai

Pyrit

HAX toolkit

Bleu

Azure

AWS

GCP

AG Grid

Job description

Role & responsibilities

• Application Development: Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, etc.
• Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.
• Implement Retrieval-Augmented Generation (RAG) & Modular RAG architectures for enhanced model performance.
• Familiarity with Multi-Modal LLM Applications.
• Fine-tune SLM(Small Language Model) for domain specific data and use cases.
• Cloud Platform Expertise: Leverage Azure, GCP, and AWS for deploying and managing GenAI applications.
• Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications.
• Front-End Integration: Implement user interfaces using front-end technologies ensuring seamless integration with GenAI backends.
• Fine-Tuning LLMs techniques & LLMOps Implementation.
• Mentorship: Guide and mentor junior developers, fostering a culture of technical excellence and innovation.

Preferred candidate profile

• Deep expertise in Python for building GenAI applications and automation tools.
• Productionization of GenAI application beyond PoCs Using scale frameworks and tools.
• LLM Frameworks: Proficiency in LLM frameworks like Autogen, Crew.ai.
• experienced in implementing architectures for handling large-scale structured and unstructured data.
• Experience with REST, SOAP, and other protocols for API integration.
• Fine-tune SLM(Small Language Model) for domain specific data and use cases.
• Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc.
• Anti-hallucination and anti-gibberish tools such as Bleu etc.
• Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development.
• Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications.
• Advanced skills in RAG and Modular RAG
• Expertise in modernizing and transforming data for GenAI applications.