AI Cloud Engineer (1099)

<p>&nbsp;</p> <h1>AI Cloud Engineers (1099-BOP)</h1> <h2>Remote</h2> <h1>Position Summary</h1> <p>Effectual AI Cloud Engineers are members of the Public Sector Program Management team responsible for ensuring that customer-facing projects are delivered with exceptional customer satisfaction and technical excellence. The AI Cloud Engineer designs, deploys, modernizes, and optimizes AI-enabled cloud environments. This role requires deep expertise in AI, cloud architecture, and AI-driven workloads in AWS environments, with demonstrated experience accelerating legacy-to-cloud migrations and advising leadership on AI strategy and vision. The position requires hands-on engineering capability, architectural oversight, and the ability to assess current-state environments and implement secure, scalable, compliant AI cloud solutions. Effectual AI Cloud Engineers are “Brand Ambassadors” and are expected to stay current on leading practices to deliver high-quality, well-conceived solutions to customers.</p> <h2>A Glimpse into the Daily Routine of an AI Cloud Engineer</h2> <p>Architect and refine AI-driven cloud solutions within AWS, deploy and optimize workloads through managed AWS AI services and containerized platforms. Modernize legacy applications, accelerate secure cloud-native migrations, and evaluate existing infrastructure to recommend AI-enabled enhancements aligned with mission objectives. Responsibilities include but not limited to implement Infrastructure as Code and CI/CD automation, integrate AI capabilities into enterprise systems and data platforms, leverage tools such as Kiro (formerly Amazon Q Developer) to enhance development efficiency, participate in architecture and security reviews, and advise technical leadership on AI strategy, roadmap execution, and cloud optimization initiatives.</p> <h2>Essential Duties and Responsibilities</h2> <ul> <li>Provide technical leadership in AI adoption strategy and recommend scalable AI solutions aligned with mission requirements</li> <li>Design and implement scalable, secure AWS AI cloud architectures and solutions</li> <li>Lead migration of legacy systems to AWS, including re-architecture, refactoring, containerization, and modernization efforts</li> <li>Deploy AI solutions using AWS services such as SageMaker, Bedrock, Kiro, Lambda, ECS, EKS, and related services</li> <li>Utilize AI-assisted engineering tools including Kiro or equivalent platforms to improve development velocity and solution quality</li> <li>Conduct performance tuning and cost optimization for AI cloud workloads</li> <li>Develop and manage Infrastructure as Code using tools like CloudFormation or Terraform</li> <li>Engineer CI/CD pipelines for AI model deployment and cloud infrastructure automation</li> <li>Implement MLOps practices including model versioning, monitoring, retraining workflows, and performance optimization</li> <li>Ensure compliance with security standards including but not limited to FedRAMP and NIST</li> <li>Assess current environments, identify architectural gaps, and implement corrective improvements</li> <li>Collaborate with cross-functional teams, at a minimum, cybersecurity, DevSecOps, and program leadership teams to maintain secure and compliant cloud ecosystems</li> <li>Provide architecture documentation, technical briefings, and implementation guidance to leadership</li> <li>Stay updated with emerging AI cloud technologies, industry trends, and best practices</li> </ul> <h2>Qualifications</h2> <ul> <li><strong><em>Minimum Education:</em></strong><strong>Bachelor’s degree&nbsp;in related discipline. <em>Certifications:</em> AWS Professional Certification(s) and AWS Certified Machine Learning - Specialty </strong><strong>AND</strong></li> <li><strong><em>Minimum Experience:</em></strong><strong> Must have a minimum of 8 years of experience in specialized AI cloud technologies including 4 years specializing in AWS AI cloud technologies</strong><strong> OR</strong></li> <li><strong><em>Substitution/Alternative to Minimum Education and Experience:</em></strong><strong> 10 years of on-the-job experience in lieu of Bachelor’s Degree</strong></li> <li><strong><u>Must be a US Citizen</u></strong></li> <li>Proven experience to architect AI solutions in secure, compliance-driven ecosystems</li> <li>Deep expertise in AWS AI services including model development, deployment, and integration</li> <li>Strong experience in cloud-native architecture, automation, and DevSecOps practices</li> <li>Proven experience modernizing legacy systems and implementing cloud transformation strategies</li> <li>Experience designing scalable AI pipelines using managed cloud services</li> <li>Strong understanding of federal security compliance frameworks and cloud governance</li> <li>Experience performing cloud cost modeling and AI workload financial optimization</li> <li>Strong problem-solving and troubleshooting skills</li> <li>Excellent communication and collaboration skills to work with cross-functional teams</li> <li>Ability to work with multiple clients, in parallel</li> <li>Ability to work Eastern Standard Time Zone schedule</li> </ul> <h2>Nice-to-Have Skills and Experience</h2> <ul> <li>Active Clearance or Public Trust (DOJ Preferred)</li> <li>Familiarity with generative AI architectures and large language model deployment</li> <li>Experience with container orchestration platforms including Kubernetes and EKS</li> <li>Strong background in DevSecOps practices within regulated government programs</li> <li>Experience integrating AI into enterprise ERP, data lake, or mission systems</li> <li>Knowledge of Zero Trust architectures within cloud environments</li> <li>Experience advising executive leadership on AI adoption strategy and digital transformation initiatives</li> </ul> <p>&nbsp;</p>