gen Ai Developer

HR Solutions; Dadri, Pune District, Mumbai; On-site; INR 400,000 - 700,000; Full time

Job summary

HR Solutions is seeking a GenAI-focused software engineer with 4+ years of hands-on experience to build scalable GenAI applications. You will design data pipelines, implement LLM-based features, and integrate front-end interfaces.

Collaborating with cross-functional teams, you will apply responsible AI practices, optimize models with PEFT/LoRA, and work with cloud platforms. The role is based in Dadri, Uttar Pradesh, India.

Qualifications

• Proficient in Python for GenAI applications and automation.
• Productionization of GenAI applications beyond PoCs using scale frameworks and tools.
• Expertise with LLM frameworks such as Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.
• Ability to design architectures for large-scale structured and unstructured data.
• Familiarity with multi-modal LLMs (text, vision, speech).
• Fine-tune SLMs for domain data using modern methods.
• Experience with PEFT, QLoRA, LoRA.
• Strong knowledge of LLMOps pipelines for CI/CD and monitoring.
• Commitment to Responsible AI practices and regulatory compliance.
• RAG and modular RAG architectures expertise.

Responsibilities

• Build GenAI applications from scratch using Autogen, LangGraph, LlamaIndex, LangChain.
• Develop high-quality, efficient Python code for GenAI solutions.
• Design architectures for handling large-scale structured and unstructured data.
• Work with multi-modal LLMs including text, vision, and speech models.
• Fine-tune LLMs for domain-specific data and use cases.
• Integrate front-end interfaces with React, Streamlit, and AG Grid.
• Design data modernization and transformation pipelines for GenAI apps.
• Apply fine-tuning techniques like PEFT, QLoRA, and LoRA.
• Set up and manage LLMOps pipelines for CI/CD and monitoring.
• Embed Responsible AI practices in the development process.
• Foster innovation through cross-functional collaboration.

Skills

GenAI Development

Python

Pipelines

LLM Frameworks

Front-End Integration

PEFT LoRA

RAG Architectures

MLOps

Cloud Platforms

Data Transformation

OCR Doc Intelligence

Data Curation

Documentation

Collaboration

Tools

Autogen

LangGraph

LlamaIndex

LangChain

Job description

Experience Required - 4+ years

Key Responsibilities:

• Application Development: Build GenAI applications from scratch using frameworks like Autogen (applied or acquired), 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.
• 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.
• 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.
• 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. (any two cloud exp.)
• Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. (any one is fine)
• 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.