Title: Sr Application Developer

Long DescriptionKey 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 experience).
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 .

Locations

• Country/Region: IN
• Requisition ID: 39596
• Work Model:
• Position Type:
• Salary Range:
• Location: INDIA - CHENNAI - BIRLASOFT OFFICE