GEN AI Developer/Prompt Engineer - Algobrain
Irving, TX 75039
About the Job
This is a Hybrid opportunity, 3 days a week onsite
We are looking for a highly skilled Generative AI Developer to join our team. The ideal candidate will be responsible for developing, optimizing, and maintaining AI-powered solutions, with a strong focus on prompt engineering and large language models (LLMs) such as GPT, Gemini, Langchain, and Llama. You will also work with advanced retrieval methods like RAG (Retrieval-Augmented Generation) and GraphRAG to enhance AI outputs and improve knowledge retrieval. You will collaborate with a multidisciplinary team of data scientists, Machine Learning engineers, and software developers to design and implement cutting-edge AI applications.
Responsibilities:
Prompt Development & Engineering:
Design and optimize effective prompts for large language models to improve output quality for various use cases.
Fine-tune prompt strategies for specific applications, including chatbots, content generation, and automated customer service.
Test and iterate on different prompt approaches to ensure alignment with project goals.
Large Language Model (LLM) & Retrieval-Augmented Generation (RAG):
Develop and fine-tune large language models like GPT, Gemini, Langchain, and Llama for specific business needs.
Implement RAG techniques to improve model outputs by integrating external knowledge from retrieval systems.
Leverage GraphRAG to enhance complex knowledge retrieval and graph-based data representation in AI models.
Stay updated on advancements in AI/LLM technologies and recommend new tools or models to enhance the AI stack.
Collaboration & Communication:
Work closely with product managers, software developers, and other stakeholders to align AI capabilities with business objectives.
Communicate technical concepts and model behavior to non-technical team members in a clear and concise manner.
Provide documentation and training to users and developers on utilizing AI models effectively.
Deployment & Monitoring:
Deploy AI models into production environments using cloud services or on-premise infrastructures.
Continuously monitor model performance, scaling solutions as needed, and ensuring models meet security and compliance standards.
Troubleshoot and optimize models for speed, accuracy, and scalability in production systems.
Required Skills:
Strong understanding of machine learning concepts, natural language processing (NLP), and generative AI.
Experience with prompt development and fine-tuning large language models like GPT, Gemini, Langchain, and Llama.
Proficiency in programming languages such as Python, with experience in AI/ML libraries (e.g., TensorFlow, PyTorch, Hugging Face).
Knowledge of MLOps tools for model deployment and monitoring.
Experience working with cloud platforms (e.g., AWS, GCP, Azure) for model training and deployment.
Preferred Qualifications:
Prior experience with Langchain for integrating LLMs into applications.
Familiarity with tools and techniques for AI model interpretability and responsible AI practices.
Strong analytical and problem-solving skills with attention to detail.
Ability to work in a fast-paced, collaborative environment.
We are looking for a highly skilled Generative AI Developer to join our team. The ideal candidate will be responsible for developing, optimizing, and maintaining AI-powered solutions, with a strong focus on prompt engineering and large language models (LLMs) such as GPT, Gemini, Langchain, and Llama. You will also work with advanced retrieval methods like RAG (Retrieval-Augmented Generation) and GraphRAG to enhance AI outputs and improve knowledge retrieval. You will collaborate with a multidisciplinary team of data scientists, Machine Learning engineers, and software developers to design and implement cutting-edge AI applications.
Responsibilities:
Prompt Development & Engineering:
Design and optimize effective prompts for large language models to improve output quality for various use cases.
Fine-tune prompt strategies for specific applications, including chatbots, content generation, and automated customer service.
Test and iterate on different prompt approaches to ensure alignment with project goals.
Large Language Model (LLM) & Retrieval-Augmented Generation (RAG):
Develop and fine-tune large language models like GPT, Gemini, Langchain, and Llama for specific business needs.
Implement RAG techniques to improve model outputs by integrating external knowledge from retrieval systems.
Leverage GraphRAG to enhance complex knowledge retrieval and graph-based data representation in AI models.
Stay updated on advancements in AI/LLM technologies and recommend new tools or models to enhance the AI stack.
Collaboration & Communication:
Work closely with product managers, software developers, and other stakeholders to align AI capabilities with business objectives.
Communicate technical concepts and model behavior to non-technical team members in a clear and concise manner.
Provide documentation and training to users and developers on utilizing AI models effectively.
Deployment & Monitoring:
Deploy AI models into production environments using cloud services or on-premise infrastructures.
Continuously monitor model performance, scaling solutions as needed, and ensuring models meet security and compliance standards.
Troubleshoot and optimize models for speed, accuracy, and scalability in production systems.
Required Skills:
Strong understanding of machine learning concepts, natural language processing (NLP), and generative AI.
Experience with prompt development and fine-tuning large language models like GPT, Gemini, Langchain, and Llama.
Proficiency in programming languages such as Python, with experience in AI/ML libraries (e.g., TensorFlow, PyTorch, Hugging Face).
Knowledge of MLOps tools for model deployment and monitoring.
Experience working with cloud platforms (e.g., AWS, GCP, Azure) for model training and deployment.
Preferred Qualifications:
Prior experience with Langchain for integrating LLMs into applications.
Familiarity with tools and techniques for AI model interpretability and responsible AI practices.
Strong analytical and problem-solving skills with attention to detail.
Ability to work in a fast-paced, collaborative environment.
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Source : Algobrain
