Cloud Engineer – AI Infrastructure

Key Responsibilities

• Design and deploy cloud-native infrastructure to support AI/ML workloads, including compute clusters, storage, networking, and security controls.
• Implement scalable environments for training, inference, and orchestration of GenAI and Agentic AI systems.
• Support hybrid cloud configurations and ensure seamless integration with cloud and on-prem systems and data sources.
• Provision and manage cloud services for AI platforms, including model registries, feature stores, and agent orchestration layers.
• Optimize cloud resources for performance, cost-efficiency, and compliance with federal standards.
• Collaborate with ML engineers to support AI/MLOps pipelines and automated deployment workflows.
• Implement cloud security best practices, including identity and access management (IAM), encryption, logging, and monitoring.
• Ensure infrastructure aligns with federal cybersecurity frameworks (e.g., FedRAMP, FISMA, NIST).
• Support auditability and traceability of AI systems, including Agentic AI agents and GenAI models.
• Develop infrastructure-as-code (IaC) templates using tools.
• Build CI/CD pipelines for cloud infrastructure provisioning and application deployment.
• Maintain system health, usage, and performance using cloud-native observability tools.
• Collaborate with AI architects, developers, and data teams to align infrastructure with solution requirements.
• Provide technical documentation and support for cloud environments and services.
• Participate in agile development cycles, sprint planning, and incident response.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• 7 years of experience in cloud engineering, infrastructure design, or DevOps.
• Proficiency with AWS cloud platforms and associated services.
• Experience supporting AI/ML workloads in cloud environments.
• Familiarity with GenAI platforms and Agentic AI system requirements.
• Strong understanding of cloud security, networking, and automation tools.
• Experience with AI/MLOps, container orchestration and serverless architectures.
• Familiarity with agent orchestration frameworks and LLM deployment strategies.

Preferred Skills

• Experience in public sector or regulated environments.
• Experience with monitoring and observability tools.

Pay

N/A

Schedule

N/A

Benefits

N/A

Ampcus is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veterans or individuals with disabilities.