Generative Ai & Agentic AI Developer

HR Solutions; Mumbai, Pune District, Bengaluru; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

HR Solutions in Mumbai seeks a GenAI Engineer to develop and productionize AI-enabled applications. You will architect data platforms, work with multi-modal LLMs, and ensure scalable deployment across cloud environments.

The role requires expertise in Python, LLM frameworks, and end-to-end AI tooling, with emphasis on RAG, PEFT, and responsible AI practices. Collaboration with frontend and backend teams is essential.

Qualifications

• Deep expertise in Python for GenAI applications and automation tools.
• Productionization of GenAI apps beyond PoCs using scale frameworks and tools.
• Proficiency in LLM frameworks like Autogen, Crew.ai, LangGraph, LlamaIndex, LangChain.

Responsibilities

• Design architectures for large-scale structured and unstructured data handling.
• Develop multi-modal LLM applications including text, vision, and speech models.
• Fine-tune Small Language Models for domain-specific data and use cases.

Skills

Python

LLM frameworks

Front-end skills

Cloud platforms

APIs

Data curation

RAG

PEFT/LoRA

Documentation

Collaboration

Tools

Autogen

Crew.ai

LangGraph

LlamaIndex

LangChain

Pylint

Pyrit

HAX toolkit

Bleu

Job description

Role & responsibilities

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.