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Job Type

Full Time

Job Description

Position Summary

Seeking an experienced (8–15 years) Python developer with strong expertise in Azure and web technologies to design, build, and deploy Generative AI/LLM-based applications. The role involves end-to-end development, fine-tuning, and integration of AI models using frameworks like LangChain and RAG for enterprise solutions.

Job Responsibilities

  • Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT
  • Software development experience in python is needed as backend for UI based applications
  • Be a part of large delivery teams working on advanced projects when expert assistance is required.
  • Deliver advanced Data Science capabilities to businesses in a meaningful manner through successful proof-of-concept solutions, and later smoothly transition the proof-of-concept into production.
  • Create Technical documents, develop, test, and deploy data analytics processes using Python, SQL on Azure/AWS platforms
  • Can interact with client on GenAI related capabilities and use cases

Education

BE/B.TechMaster of Computer Application

Work Experience

  • Require 8-15 years experience to develop, test, and deploy Python based applications on Azure platforms
  • Must have basic knowledge on concepts of Generative AI / LLMs / GPT
  • Deep understanding of architecture and work experience on Web Technologies
  • Python, SQL hands-on experience
  • Good to have Databricks Genie
  • Design and develop LLM-based systems:
  • Build and deploy Generative AI solutions, often using frameworks like Langchain and techniques like Retrieval-Augmented Generation (RAG).
  • Model development and fine-tuning: Train, fine-tune, and refine large language models to meet specific business requirements or improve performance on particular tasks.
  • Integration: Collaborate with cross-functional teams to integrate LLM models into broader applications and products.
  • Prompt engineering: Develop and implement effective prompts to guide the LLM and improve the accuracy and relevance of its outputs.

Behavioural Competencies

OwnershipTeamwork & LeadershipCultural FitMotivation to Learn and Grow

Technical Competencies

Problem SolvingAzure SQLDatabricksPython

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