Senior Application Developer - GenAI and Large-Scale Data Solutions

Birlasoft Limited; Chennai; On-site; INR 1,800,000 - 3,000,000; Full time

Job summary

Birlasoft Limited seeks a Sr Application Developer to design and build GenAI applications from scratch using Autogen, LangGraph, LangChain, LlamaIndex and related tooling. You will develop Python code, create front-end interfaces with React/Streamlit, and architect data pipelines for large-scale data processing.

You will also fine-tune LLMs, implement LLMOps pipelines, and ensure responsible AI practices across projects, collaborating with cross-functional teams to deliver scalable GenAI

Qualifications

• Deep expertise in Python for GenAI applications and automation tools.
• Productionization of GenAI applications beyond PoCs using scale frameworks and tooling.
• Proficiency with GenAI frameworks like Autogen, LangGraph, LangChain, LlamaIndex.
• Design architectures for large-scale structured and unstructured data.
• Familiarity with multi-modal LLMs including text, vision, and speech models.
• Mastery of fine-tuning techniques (PEFT, QLoRA, LoRA).
• Experience with LLMOps pipelines for CI/CD, deployment, and monitoring.
• Ability to implement responsible AI practices and regulatory compliance.

Responsibilities

• Build GenAI applications from scratch using listed frameworks.
• Develop high-quality Python code for GenAI solutions.
• Design architectures for large-scale data handling.
• Create multi-modal LLM applications (text, vision, speech).
• Fine-tune LLMs for domain-specific use cases.
• Integrate front-end interfaces with React/Streamlit/AG Grid.
• Design data modernization and transformation pipelines.
• Apply fine-tuning techniques (PEFT, QLoRA, LoRA).
• Set up LLMOps for CI/CD, deployment, monitoring.
• Embed Responsible AI practices throughout development.
• Collaborate with cross-functional teams on product delivery.

Skills

Python programming

LLM frameworks

Front-end integration

Large-scale data handling

LLMOps

Responsible AI

RAG

Data modernization

OCR & document intelligence

API integration

Data curation

Technical documentation

Collaboration

Tools

Autogen

Crew.ai

LangGraph

LangChain

LlamaIndex

Pyrit

Pylint

LoRA

PEFT

Azure

GCP

AWS

React

Streamlit

AG Grid

Job description

Sr Application Developer Long Description ________________________________________

Key Responsibilities:

• 1. Application Development: Build GenAI applications from scratch using frameworks like Autogen (applied or acquired), Crew.ai, LangGraph, LlamaIndex, and LangChain.
• 2. Python Programming: Develop high-quality, efficient, and maintainable Python code for GenAI solutions.
• 3. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
• 4. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
• 5. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
• 6. Front-End Integration: Implement user interfaces using front-end technologies like React, Streamlit, and AG Grid, ensuring seamless integration with GenAI backends.
• 7. Data Modernization and Transformation: Design and implement data modernization and transformation pipelines to support GenAI applications.
• 8. Fine-Tuning LLMs: Apply fine-tuning techniques such as PEFT, QLoRA, and LoRA to optimize LLMs for specific use cases.
• 9. LLMOps Implementation: Set up and manage LLMOps pipelines for continuous integration, deployment, and monitoring.
• 10. Responsible AI Practices: Ensure ethical AI practices are embedded in the development process.
• 11. innovation.

Required Skills :

• 1. Python Programming: Deep expertise in Python for building GenAI applications and automation tools.
• 2. Productionization of GenAI application beyond PoCs – Using scale frameworks and tools such as Pylint,Pyrit etc.
• 3. LLM Frameworks: Proficiency in frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, and LangChain.
• 4. Large-Scale Data Handling & Architecture: Design and implement architectures for handling large-scale structured and unstructured data.
• 5. Multi-Modal LLM Applications: Familiarity with text chat completion, vision, and speech models.
• 6. Fine-tune SLM(Small Language Model) for domain specific data and use cases.
• 7. Prompt injection fallback and RCE tools such as Pyrit and HAX toolkit etc.
• 8. Anti-hallucination and anti-gibberish tools such as Bleu etc.
• 9. Front-End Technologies: Strong knowledge of React, Streamlit, AG Grid, and JavaScript for front-end development.
• 10. Cloud Platforms: Extensive experience with Azure, GCP, and AWS for deploying and managing GenAI applications. (any two cloud exp.)
• 11. Fine-Tuning Techniques: Mastery of PEFT, QLoRA, LoRA, and other fine-tuning methods. (any one is fine)
• 12. LLMOps: Strong knowledge of LLMOps practices for model deployment, monitoring, and management.
• 13. Responsible AI: Expertise in implementing ethical AI practices and ensuring compliance with regulations.
• 14. RAG and Modular RAG: Advanced skills in Retrieval-Augmented Generation and Modular RAG architectures.
• 15. Data Modernization: Expertise in modernizing and transforming data for GenAI applications.
• 16. OCR and Document Intelligence: Proficiency in OCR and document intelligence using cloud-based tools.
• 17. API Integration: Experience with REST, SOAP, and other protocols for API integration.
• 18. Data Curation: Expertise in building automated data curation and preprocessing pipelines.
• 19. Technical Documentation: Ability to create clear and comprehensive technical documentation.
• 20. Collaboration and Communication: Strong collaboration and communication skills to work effectively with cross-functional teams.

Target Companies – Quantiphi,Datastax,Coforge,HCL,Accenture,Fractal.

Area(s) of responsibility . Experience Level Senior Level