AI/Machine Learning Engineer

- Apply responsible AI principles fairness transparency explainability reliability human oversight - Build AI model deployment pipelines and model lifecycle - Build and maintain AI services APIs microservices - Conduct technical reviews and implementation planning - Design and develop data pipelines for training and inference - Design develop test deploy AI ML models - Develop prompt engineering evaluation optimization - Ensure alignment with AI governance security privacy and data protection - Implement Retrieval-Augmented Generation architectures - Implement automated testing deployment monitoring model versioning release management - Implement generative AI agentic AI solutions - Implement observability and monitoring frameworks for AI workloads - Integrate AI solutions with enterprise applications cloud APIs databases data warehouses - Investigate production issues perform root cause analysis implement corrective actions - Monitor model performance accuracy reliability cost and stability - Perform data preparation feature engineering and model operationalization - Support AI risk assessments security reviews compliance documentation - Support production deployment aligned to enterprise architecture - Tune and optimize models for performance quality and usability