GenAI Developer
Experience Range – 10+ Years
Location : Houston , TX
Essential Job Functions & Responsibilities
GenAI Application Development: Design, develop, and deploy cutting-edge GenAI applications, such as conversational chatbots, that provide exceptional user experiences.
Proof of Concept to Production: Collaborate with cross-functional teams taking existing proof of concepts to production.
Hands-On Development: Write clean, efficient, and maintainable code primarily using python and object-oriented design frameworks, and Azure technologies.
Team Collaboration: Work closely with a talented team of developers to share knowledge, solve complex problems, and deliver high-quality solutions.
Skills, Experience & Education Requirements
Python Proficiency: 10+ years of experience in software development. Strong proficiency in Python programming, with experience in object-oriented frameworks and the entire software development lifecycle.
GenAI Expertise: At least 5 years of experience in AI, with a minimum of 2 years focused on Generative AI.
LLM Proficiency: At least 1 year of hands-on experience interfacing with and leveraging Large Language Models (LLMs).
GenAI Production Experience: Proven track record of implementing at least 1 production-grade Generative AI solution like a conversation chatbot with large language models at enterprise level.
Azure Mastery: Deep practical experience with Azure, including Function Apps, APIM, and App Insights.
GenAI Model Expertise: Familiarity with one or more of the following: Azure OpenAI models, Google Gemini model variants.
Application Development: Knowledge of Langchain or similar application development libraries.
Multi-Agent Frameworks: Understanding of multi-agent frameworks for designing and deploying complex applications.
GenAI Fundamentals: General understanding of Generative AI models, concepts, capabilities, and usage patterns including retrieval augmented generation, chunking, finetuning.
Nice-to-have Requirements
C# nice to have
API Development: Experience in developing and managing APIs.
Multi-Agent Solutions: Implementation of at least one production-level GenAI solution using multi-agent frameworks.
Multiple Production Solutions: Experience implementing more than one production-grade Generative AI solution.