AI Cloud Engineer (1099-BOP)

AI Cloud Engineers (1099-BOP)

Remote

Position Summary

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.

A Glimpse into the Daily Routine of an AI Cloud Engineer

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.

Essential Duties and Responsibilities

• Provide technical leadership in AI adoption strategy and recommend scalable AI solutions aligned with mission requirements

• Design and implement scalable, secure AWS AI cloud architectures and solutions

• Lead migration of legacy systems to AWS, including re-architecture, refactoring, containerization, and modernization efforts

• Deploy AI solutions using AWS services such as SageMaker, Bedrock, Kiro, Lambda, ECS, EKS, and related services

• Utilize AI-assisted engineering tools including Kiro or equivalent platforms to improve development velocity and solution quality

• Conduct performance tuning and cost optimization for AI cloud workloads

• Develop and manage Infrastructure as Code using tools like CloudFormation or Terraform

• Engineer CI/CD pipelines for AI model deployment and cloud infrastructure automation

• Implement MLOps practices including model versioning, monitoring, retraining workflows, and performance optimization

• Ensure compliance with security standards including but not limited to FedRAMP and NIST

• Assess current environments, identify architectural gaps, and implement corrective improvements

• Collaborate with cross-functional teams, at a minimum, cybersecurity, DevSecOps, and program leadership teams to maintain secure and compliant cloud ecosystems

• Provide architecture documentation, technical briefings, and implementation guidance to leadership

• Stay updated with emerging AI cloud technologies, industry trends, and best practices

Qualifications

• Minimum Education:Bachelor’s degree in related discipline. Certifications: AWS Professional Certification(s) and AWS Certified Machine Learning - Specialty AND

• Minimum Experience: Must have a minimum of 8 years of experience in specialized AI cloud technologies including 4 years specializing in AWS AI cloud technologies OR

• Substitution/Alternative to Minimum Education and Experience: 10 years of on-the-job experience in lieu of Bachelor’s Degree

• Must be a US Citizen

• Proven experience to architect AI solutions in secure, compliance-driven ecosystems

• Deep expertise in AWS AI services including model development, deployment, and integration

• Strong experience in cloud-native architecture, automation, and DevSecOps practices

• Proven experience modernizing legacy systems and implementing cloud transformation strategies

• Experience designing scalable AI pipelines using managed cloud services

• Strong understanding of federal security compliance frameworks and cloud governance

• Experience performing cloud cost modeling and AI workload financial optimization

• Strong problem-solving and troubleshooting skills

• Excellent communication and collaboration skills to work with cross-functional teams

• Ability to work with multiple clients, in parallel

• Ability to work Eastern Standard Time Zone schedule

Nice-to-Have Skills and Experience

• Active Clearance or Public Trust (DOJ Preferred)

• Familiarity with generative AI architectures and large language model deployment

• Experience with container orchestration platforms including Kubernetes and EKS

• Strong background in DevSecOps practices within regulated government programs

• Experience integrating AI into enterprise ERP, data lake, or mission systems

• Knowledge of Zero Trust architectures within cloud environments

• Experience advising executive leadership on AI adoption strategy and digital transformation initiatives