Summary: Lead cloud-native AI/ML product development on AWS, focusing on optimization and forecasting for energy clients, while staying hands-on with SageMaker and Bedrock. Highlights: 1. Lead design, build, and rollout of optimization and forecasting models on AWS. 2. Drive generative AI using Amazon Bedrock for document processing and automation. 3. Collaborate with clients and AWS Professional Services to align solutions. We are building cloud\-native AI/ML products on AWS that deliver optimization and forecasting value for energy (oil \& gas) clients at scale. As the **Chief Data Science Engineer (AWS SageMaker \& Bedrock)**, you will lead multiple parallel engagements while staying hands\-on with SageMaker, Bedrock, and production MLOps. Bring your leadership and delivery mindset and apply today. **Responsibilities** * Lead the design, build, and rollout of optimization and forecasting models on Amazon SageMaker * Develop end\-to\-end ML workflows covering data preparation, feature engineering, training, evaluation, and inference * Architect scalable, cost\-efficient, production\-grade inference solutions aligned with AWS best practices * Use Amazon Bedrock to deliver generative AI for document processing, knowledge extraction, and automation * Drive technical choices across workstreams and provide escalation support for AI/ML topics * Coordinate delivery across multiple parallel engagements and manage priorities and timelines * Collaborate with client data teams, domain experts, and AWS Professional Services to align solutions to business goals * Implement monitoring, logging, and model governance using AWS\-native tooling * Apply AWS Well\-Architected Framework principles focused on security, reliability, performance, and cost optimization * Document model architectures, pipeline configurations, and operational procedures for maintainability * Deliver knowledge transfer sessions and create handover materials to enable client self\-sufficiency **Requirements** * 7\+ years of experience in data science and machine learning solutions development * Hands\-on experience with Amazon SageMaker for training, hosting, and pipelines * Solid background in building optimization and forecasting models * Proven leadership experience running multiple parallel client engagements * Strong stakeholder management skills with executive\-level communication * Deep understanding of AWS cloud\-native best practices for production AI/ML solutions * Demonstrated MLOps skills spanning data preparation, feature engineering, evaluation, and inference * Advanced energy domain experience in oil \& gas or industrial AI/ML use cases * Excellent problem\-solving ability with confidence operating independently across workstreams * Upper\-Intermediate English proficiency (B2, Upper\-Intermediate) **Nice to have** * Experience with Amazon Lookout for anomaly detection on industrial or operational data