AWS solution Architect Cloud Engineer

This range is provided by Medai Digital. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

$/yr - $/yr

Company Description

Medai Digital is a leading technology, information, and media company with a strong presence across Houston, Austin, Los Angeles, and the Bay Area. We specialize in applying advanced Artificial Intelligence and physics-based solutions to drive transformative outcomes across pivotal sectors, including Real Estate, Oil & Gas, Energy, Sustainable & Green Solutions, Marketing, Healthcare, and Finance. Our mission is to empower organizations through innovative hybrid models that seamlessly integrate deep scientific principles, engineering expertise, and cutting-edge AI with robust data technology.

These intelligent solutions are designed to achieve significant cost optimization, effective risk mitigation, unparalleled opportunity unlocking, and accelerated market expansion. Founded by seasoned scientists with PhDs in physics, engineering, and computer science, our team brings extensive experience from both academia and industry, backed by a proven track record of successful AI, engineering, and simulation product deliveries. We deliver our expertise through strategic consulting services and by leading the charge in Software as a Service (SaaS) and Agent (AI) as a Service (AAAS) platforms.

About This Role:

Medai Digital is seeking an accomplished AWS Solution Architect & Cloud Engineer to join our innovative team. This pivotal role involves designing, building, and optimizing our cloud infrastructure on AWS to support complex AI and Large Language Model (LLM) ecosystems, and manage grand-scale databases. A key focus will be on driving maximum cost efficiency while maintaining high performance, scalability, and security for our cutting-edge AI services.

You will play a crucial role in architecting cloud solutions that power our SaaS and AAAS platforms, enabling our scientists and engineers to deliver transformative solutions across diverse industries.

Key Responsibilities:

• Design and implement highly scalable, secure, and cost-optimized cloud architectures on AWS for AI/ML workloads, LLM inference/training, and big data solutions.
• Evaluate, select, and integrate appropriate AWS services (e.g., EC2, S3, RDS, Dynamo
  
  DB, Lambda, Sage Maker, EKS, ECS, VPC, Cloud Formation, etc.) to meet specific project requirements while ensuring cost-effectiveness.
• Develop and manage CI/CD pipelines for cloud deployments, ensuring automation, efficiency, and reliability.
• Implement robust monitoring, logging, and alerting solutions to ensure the health, performance, and cost visibility of cloud resources.
• Optimize existing cloud infrastructure and processes to identify and implement cost-saving measures without compromising performance or security.
• Collaborate closely with Data Scientists, Data Engineers, Software Engineers, and Product Owners to translate complex AI/ML requirements into scalable cloud infrastructure designs.
• Manage and optimize large-scale databases (relational, No
  
  SQL, data warehouses) on AWS to support high-throughput data pipelines for AI/ML.
• Ensure adherence to security best practices, compliance standards, and disaster recovery strategies within the AWS environment.
• Stay abreast of the latest AWS service updates, cloud architecture patterns, AI/ML advancements, and cost optimization techniques.
• Provide technical guidance and mentorship to other team members on AWS best practices and cloud native development.

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, or a related technical field.
• 5+ years of experience in cloud architecture, engineering, and operations, with at least 3 years focused on AWS.
• Deep familiarity with the AWS cloud ecosystem, including compute, storage, networking, security, database, and analytics services.
• Proven experience in designing and implementing cost-effective cloud solutions for AI/ML workloads and large datasets.
• Strong understanding of containerization technologies (Docker, Kubernetes/EKS) and serverless architectures (Lambda).
• Proficiency in Infrastructure as Code (IaC)…