Gen AI Developer

VirtusaIrving, TX

About The Position

We are seeking an experienced Gen AI Developer with a strong focus on generative model architecture and tools. The ideal candidate will have a good understanding of machine learning principles, algorithms, and statistical modeling, with extensive experience in Generative AI models such as Large Language Models and image generation models. You will be responsible for developing and deploying Generative AI applications, working with agentic AI stacks, and contributing to large microservice-based architecture applications. Strong analytical, problem-solving, and communication skills are essential for this role.

Requirements

  • Proficient in Python with 5+ years of hands-on experience.
  • Extensive experience with Generative AI models (e.g., Large Language Models, image generation models).
  • Proven experience with Agentic AI stacks, including frameworks for building autonomous agents, planning, memory, and tool use.
  • Hands-on experience with prompt engineering, model fine-tuning, and deployment of Generative AI applications.
  • Hands-on experience with GitHub, Confluence, JIRA, Jenkins, CI/CD tools.
  • Experience working with large microservice-based architecture applications.
  • Understanding of data architectures, data pipelines, and data governance in an AI context.
  • Good analytical and problem-solving skills.
  • Strong verbal and written communication skills.

Nice To Haves

  • Experience in machine learning or AI development.
  • Good understanding of machine learning principles, algorithms, and statistical modeling.
  • Familiarity with tools and technologies like LangChain and agent development.

Responsibilities

  • Develop and deploy Generative AI applications.
  • Implement and optimize generative model architectures.
  • Utilize tools and technologies like LangChain for agent development.
  • Apply prompt engineering and model fine-tuning techniques.
  • Work with agentic AI stacks, including frameworks for building autonomous agents, planning, memory, and tool use.
  • Collaborate on large microservice-based architecture applications.
  • Ensure understanding and application of data architectures, data pipelines, and data governance in an AI context.
  • Troubleshoot and resolve complex technical challenges related to AI development.
  • Communicate complex technical concepts to diverse audiences.
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