Cloud Engineer

Maganti IT Resources, LLC; United States; Remote; USD 140,000 - 200,000; Full time

Job summary

Maganti IT Resources, LLC is seeking a Remote Cloud AI Platform Engineer to design, deploy, and manage enterprise AI solutions on AWS using Bedrock and Claude APIs. You will implement secure, scalable AI platforms with governance and cost controls, while collaborating with architects, data engineers, and DevOps teams.

The role requires deep cloud engineering expertise, API development, and strong problem-solving and communication skills to support model lifecycle and performance tuning across

Qualifications

• 12+ years of experience in Cloud/DevOps engineering.
• Hands-on AWS Cloud Services expertise (EC2, S3, IAM).
• Experience with Amazon Bedrock and Anthropic Claude APIs.
• Strong API development and integration skills.
• Security controls, governance, and cost management knowledge.

Responsibilities

• Design, deploy, and manage AI solutions on AWS using Bedrock and Claude APIs.
• Integrate AI capabilities into enterprise applications and workflows.
• Configure IAM, security policies, and governance controls.
• Develop and manage API integrations between AI platforms and systems.
• Monitor, log, optimize performance, and provide ops support.
• Establish usage management and cloud cost optimization strategies.
• Ensure compliance with security, privacy, and regulatory requirements.
• Collaborate with cloud architects, data engineers, and DevOps teams.

Skills

Cloud engineering

DevOps

IAM & security

API development

Governance & compliance

Cost optimization

Monitoring & logging

Technical documentation

Communication

Troubleshooting

Tools

AWS Cloud Services

Terraform

CloudFormation

Bedrock & Claude APIs

RESTful APIs

Kubernetes/Docker

CI/CD pipelines

Job description

Job Title : Cloud AI Platform Engineer

Location : Remote

Contract

We are seeking a highly skilled Cloud AI Platform Engineer to design, deploy, and manage enterprise AI solutions leveraging Anthropic Claude, Amazon Bedrock, and AWS cloud services. The ideal candidate will be responsible for implementing secure, scalable, and cost-effective AI platforms while ensuring governance, compliance, and operational excellence. This role requires expertise in cloud engineering, AI/ML platform integration, API development, security controls, and cloud cost management.

Key Responsibilities

• Design, deploy, and manage AI solutions using Amazon Bedrock, Claude APIs, and AWS services.
• Integrate Generative AI capabilities into enterprise applications and business workflows.
• Configure and maintain Identity and Access Management (IAM), security policies, and governance controls.
• Develop and manage API integrations between AI platforms, cloud services, and enterprise systems.
• Implement monitoring, logging, performance optimization, and operational support processes.
• Establish usage management, financial controls, and cloud cost optimization strategies.
• Ensure compliance with enterprise security, privacy, and regulatory requirements.
• Collaborate with cloud architects, data engineers, DevOps teams, and business stakeholders.
• Troubleshoot platform issues and provide technical guidance on AI infrastructure and deployment best practices.
• Support AI model lifecycle management, performance tuning, and operational governance.

Required Qualifications

• 12+ years of experience in Cloud Engineering, DevOps, or Infrastructure Engineering.
• Hands‑on experience with AWS Cloud Services (EC2, Lambda, S3, VPC, CloudWatch, IAM).
• Strong experience with Amazon Bedrock and Generative AI platforms.
• Experience integrating Anthropic Claude APIs and Large Language Models (LLMs).
• Proficiency in API development and integration using RESTful services.
• Strong understanding of cloud security, IAM, encryption, networking, and compliance frameworks.
• Experience with Infrastructure as Code (Terraform, CloudFormation, or similar tools).
• Knowledge of CI/CD pipelines and DevOps practices.
• Experience monitoring cloud resources and optimizing cloud costs.
• Strong troubleshooting, documentation, and communication skills.

Preferred Qualifications

• Experience with Azure OpenAI, Google Vertex AI, or other AI platforms.
• Knowledge of MLOps practices and AI governance frameworks.
• Experience implementing Responsible AI and AI security controls.
• Familiarity with Kubernetes, Docker, and containerized workloads.
• Experience in regulated industries such as Healthcare, Life Sciences, or Pharmaceuticals.
• AWS Certifications such as AWS Solutions Architect, AWS DevOps Engineer, or AWS Machine Learning Specialty.