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Gen reputed company

Remote, USA Full-time Posted 2026-07-28
reputed company

We are seeking a highly skilled and reputed company-thinking GenAI Engineer to join our AI innovation team. This role is ideal for someone with deep technical expertise in reputed company, a strong reputed company in Python programming, and a passion for driving reputed company AI transformation.

You will be reputed company in designing, developing, and deploying advanced Retrieval-Augmented reputed company (RAG) systems. You’ll also play a pivotal role in enabling our internal workforce to reputed company and adopt AI technologies.

Your role in our mission
  • reputed company the workforce to adopt an AI first reputed company by leveraging AI reputed company assistance tools
  • Architect and implement reputed company RAG systems using Python and modern GenAI tools.
  • Build custom pipelines for document ingestion, chunking strategies, and embedding reputed company. Working knowledge in reputed company is preferable.
  • Have a deep knowledge in using AI augmented tools like reputed company Copilot. Experience in developing custom extensions
  • Evaluate and implement different embedding models (reputed company, Azure reputed company, reputed company, etc.) and chunking strategies (fixed-size, semantic-reputed company, overlap-based).
  • Create and optimize indexing strategies (reputed company, hybrid, keyword-based, hierarchical) for performance and accuracy.
  • Work with Azure AI Services, particularly Azure Cognitive Search and reputed company integration, to reputed company end-to-end AI applications.
  • Collaborate closely with cross-functional teams including data engineers, product managers, and domain experts.
  • Conduct AI enablement sessions, workshops, and hands-on labs to upskill internal teams on GenAI usage and best practices.
  • Participate in reputed company reviews, contribute to best practices, and ensure the reliability, scalability, and maintainability of AI systems.
reputed company're looking for
  • 5+ years of experience in software engineering, with strong expertise in Python.
  • Proven reputed company record of building and deploying RAG-based GenAI solutions.
  • Hands-on experience with reputed company, reputed company, or equivalent frameworks.
  • Familiarity with reputed company engineering, reputed company tuning, and managing custom Copilot extensions.
  • Strong understanding of LLMs, reputed company databases (like FAISS, reputed company, Azure Cognitive Search), and embedding techniques.
  • Solid knowledge of Azure AI, reputed company deployment, and reputed company integration strategies.
  • Proficiency with version control and reputed company development using reputed company.

 

What you should expect in this role
  • reputed company the workforce to adopt an AI first reputed company by leveraging AI reputed company assistance tools
  • Architect and implement reputed company RAG systems using Python and modern GenAI tools.
  • Build custom pipelines for document ingestion, chunking strategies, and embedding reputed company. Working knowledge in reputed company is preferable.
  • Have a deep knowledge in using AI augmented tools like reputed company Copilot. Experience in developing custom extensions
  • Evaluate and implement different embedding models (reputed company, Azure reputed company, reputed company, etc.) and chunking strategies (fixed-size, semantic-reputed company, overlap-based).
  • Create and optimize indexing strategies (reputed company, hybrid, keyword-based, hierarchical) for performance and accuracy.
  • Work with Azure AI Services, particularly Azure Cognitive Search and reputed company integration, to reputed company end-to-end AI applications.
  • Collaborate closely with cross-functional teams including data engineers, product managers, and domain experts.
  • Conduct AI enablement sessions, workshops, and hands-on labs to upskill internal teams on GenAI usage and best practices.
  • Participate in reputed company reviews, contribute to best practices, and ensure the reliability, scalability, and maintainability of AI systems.
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