Gen AI

SheJobs Group; India; A distancia; INR 3.000.000 - 6.000.000; Jornada completa

Descripción de la vacante

SheJobs Group is seeking a Technical Lead to develop GenAI applications using leading LLM frameworks. You will design scalable data architectures and implement end-to-end solutions with Python, cloud platforms, and modern front-end integrations.

The role involves mentoring junior developers, collaborating with cross-functional teams, and applying responsible AI practices. Experience with Autogen, LangChain, LangGraph, and related tools is highly valued.

Formación

• Python programming expertise for GenAI applications.
• Productionization of GenAI apps using scale frameworks and tooling.
• LLM frameworks: Autogen, Crew.ai, LangGraph, LlamaIndex, LangChain.
• Large-scale data handling and architecture for structured/unstructured data.
• Multi-modal LLM applications including text, vision and speech models.
• Front-end integration with React, Streamlit, and AG Grid.
• Data modernization and transformation pipelines for GenAI apps.
• OCR and document intelligence using cloud-based tools.
• API integration via REST/SOAP and other protocols.

Responsabilidades

• Build GenAI applications from scratch using the listed frameworks.
• Design architectures for large-scale data handling and processing.
• Develop Python code for GenAI solutions and automation.
• Implement front-end integrations for seamless user experiences.
• Apply PEFT/QLoRA/LoRA for fine-tuning LLMs.
• Set up LLMOps pipelines for CI/CD and monitoring.
• Ensure responsible AI practices are embedded in development.
• Collaborate with data scientists, engineers and product managers.

Conocimientos

Python Programming

LLM Frameworks

Data Architecture

Multi-Modal LLM

Front-End Tech

Cloud Platforms

Fine-Tuning

LLMOps

Responsible AI

RAG

Data Modernization

OCR & Document Intelligence

API Integration

Data Curation

Technical Documentation

Collaboration & Mentorship

Productionization

Pyrit

Bleu

HAX toolkit

Pylint

Herramientas

Autogen

Crew.ai

LangGraph

LlamaIndex

LangChain

Pyrit

Pylint

Bleu

HAX toolkit

Descripción del empleo

About the Role

Experience: 6.5+ Years

The Technical Lead will focus on the development, implementation, and engineering of GenAI applications using the latest LLMs and frameworks. This role requires hands-on expertise in Python programming, cloud platforms, and advanced AI techniques, along with additional skills in front-end technologies, data modernization, and API integration. The Technical Lead will be responsible for building applications from the ground up, ensuring robust, scalable, and efficient solutions.

Key Responsibilities:

Application Development: Build GenAI applications from scratch using frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.

Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.

Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.

Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.

Fine-tune SLM(Small Language Model) for domain specific data and use cases.

Front-End Integration: Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with GenAI backends.

Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications.

OCR and Document Intelligence: Develop solutions for Optical Character Recognition (OCR) and document intelligence using cloud-based tools.

API Integration: Use REST, SOAP, and other protocols to integrate APIs for data ingestion, processing, and output delivery.

Cloud Platform Expertise: Leverage Azure, GCP, and AWS for deploying and managing GenAI applications.

Fine-Tuning LLMs: Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases.

LLMOps Implementation: Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.

Responsible AI Practices: Ensure ethical AI practices are embedded in the development process.

RAG and Modular RAG: Implement Retrieval-Augmented Generation (RAG) and Modular RAG architectures for enhanced model performance.

Data Curation Automation: Build tools and pipelines for automated data curation and preprocessing.

Technical Documentation: Create detailed technical documentation for developed applications and processes.

Collaboration: Work closely with cross-functional teams, including data scientists, engineers, and product managers, to deliver high-impact solutions.

Mentorship: Guide and mentor junior developers, fostering a culture of technical excellence and innovation.

Required Skills :

Python Programming: Deep expertise in Python for building GenAI applications and automation tools.

Productionization of GenAI application beyond PoCs – Using scale frameworks and tools such as Pylint,Pyrit etc.

LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.

Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.

Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.

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.

Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications.

Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods.

LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.

Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.

RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.

Data Modernization: Expertise in modernizing and transforming data for GenAI applications.

OCR and Document Intelligence: Proficiency in OCR and document intelligence using cloud-based tools.

API Integration: Experience with REST, SOAP, and other protocols for API integration.

Data Curation: Expertise in building automated data curation and preprocessing pipelines.

Technical Documentation: Ability to create clear and comprehensive technical documentation.

Collaboration and Communication: Strong collaboration and communication skills to work effectively with cross-functional teams.

Mentorship: Proven ability to mentor junior developers and foster a culture of technical excellence.

Skills & Technologies

Required Skills

Python Programming expert LLM Frameworks expert Large-Scale Data Handling & Architecture expert Multi-Modal LLM Applications expert Front-End Technologies expert Cloud Platforms expert Fine-Tuning Techniques expert LLMOps expert

Nice to Have

Responsible AI Practices RAG and Modular RAG Data Curation Automation