Senior Software Engineer - Python Hybrid - Costa Mesa, CA or Allen, TX 1 day/week 12+ month contract Required Skills: • Amazon Web Services (AWS) • Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework • Strong experience with MLOps platforms such as AWS Sagemaker, Kubeflow, or MLflow. • Development experience using Python, Flask, Django, AsyncIO, etc. • Experience in monitoring the health of distributed systems and a strategy for error detection and recovery • Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices • Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate ...etc.) • Demonstrable familiarity with CI/CD process, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.) • Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS. Responsibilities What you’ll be doing: • Partners with Architecture/Product/CloudOps/Engineering teams to craft highly scalable, flexible and resilient cloud architectures that address customer business problems and accelerate the adoption of cloud services. • Designs and implements complex architectural solutions using AWS design principles, best practices, and industry standards. • Build scalable, reliable, and cost-efficient ML pipelines using Python, AWS services (SageMaker, Lambda, Step Functions, S3, ECR, etc.), and container technologies (Docker, ECS/Fargate). • Lead technical design reviews, guide engineering teams on architectural best practices, and create high-level and low-level design documents. • Determines code quality and test coverage, designs and implements tests to make sure software is built to the highest quality possible. • Communicate and explain technical/architectural decisions to product, development, and delivery teams • Drive continual improvement in quality and efficiency, including defect prevention/root cause analysis, as well as suggest and adopt improvements to technology and efficiency. • Perform proof of concept work for integrating new technologies into the existing product. • Ability to comprehend detailed project specifications, as well as the ability to adapt to various technologies and simultaneously work on multiple projects. • Participates in reviews of software engineers’ code to deliver high-quality solutions. • Work closely with the product and actively participate in business requirement analysis. • Lead and mentor junior members of the team. • Research and implement performance tuning and enhancements to existing and newly developed systems to gain the most performance from the existing Infrastructure. Knowledge, Experience & Qualifications What your background looks like: • BS in Computer Science or related fields; MS preferred • 8+ years’ experience in key engineering roles, such as technical lead, software engineer, and software architect. • 5+ years’ experience using Amazon Web Services (AWS) to architect and deploy reliable, cost-effective, scalable, and secure cloud native solutions. Experience working in an agile / scrum environment • Deep understanding of cloud computing technologies and workload transition challenges, knowledge of AWS Well-Architected Framework, industry standards, and best practices • Strong experience with MLOps platforms such as AWS Sagemaker, Kubeflow, or MLflow. • Hands-on design and development experience using Python, Flask, Django, AsyncIO, etc. • Good understanding of distributed software applications, including system integration, testing, and troubleshooting • Experience in monitoring the health of distributed systems and a strategy for error detection and recovery • Systems integration experience, including design and development of APIs, Real-Time Systems, and Microservices • Current cloud technology experience, preferably AWS (EKS, S3, RDS, Lambda, Aurora, ECS-Fargate ...etc.) • Passionate to learn new frameworks, building new processes and procedures from scratch, and training the analysts on best practices. • Demonstrable familiarity with CI/CD process, testing frameworks, and practices (CodeCommit, CodeDeploy, CodePipeline, Jenkins, Harness, etc.) • Experience integrating with async messaging, logging, or queues, such as Kafka, RabbitMQ, or SQS. • Strong knowledge of software development process and project management methodologies. • Strong problem-solving and analytical skills. • Excellent communication and documentation skills with the ability to lead cross-functional initiatives. • Enjoy working in a dynamic, fast-moving, and challenging environment • Good team player and work with globally distributed teams. Nice to have • Experience with monitoring and logging tools - Dynatrace, Splunk etc. • Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn. • Experience with Kubeflow, MLflow, Airflow, or similar workflow orchestration tools. • Building automated and scheduled pipelines for analytical processes.