AI Senior Engineer

Responsibilities: 1. AI Solution Development: 1.1. Develop AI-powered solutions to improve software quality assurance processes. 1.2. Leverage frameworks like Retrieval-Augmented Generation (RAG) and other state-of-the-art AI/ML frameworks to design innovative testing and debugging tools. 1.3. Create models for triaging and debugging test case failures using structured and unstructured data, such as log files. 2. Framework Optimization: 2.1. Enhance testing processes with AI to automate root-cause analysis, bug detection, and recommendation systems. 2.2. Collaborate with cross-functional teams to integrate AI solutions into existing software testing pipelines. 3. MLOps Development: 3.1. Design, implement, and maintain robust MLOps pipelines for continuous integration and deployment of AI/ML models. 3.2. Automate workflows for model training, evaluation, and deployment. Mandatory Skills: Artificial Intelligence (AI) Langchain MLFlow Python TensorFlow Mandatory Skills Description: - Strong knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). - Experience with MLOps tools (e.g., MLflow, Kubeflow, AWS Bedrock, SageMaker). - Proficiency in RAG frameworks and understanding of knowledge-based systems. - Familiarity with LangChain and Hugging Face Transformers. Experience working with Streamlit. - Strong command on all AWS services and prompt engineering techniques and Dspy. - Familiarity with cloud platforms (e.g., AWS, GCP, Azure). - Knowledge of SQL and database management for test data validation. - Strong debugging and troubleshooting skills in software systems.

Location: Mexico, MX

Posted Date: 7/22/2025