Cloud Engineer

Ampcus is seeking a skilled and experienced Cloud Engineer to design, implement, and manage cloud infrastructure supporting AI and ML workloads for a leading independent federal agency focused on financial system stability. This role will be critical in enabling scalable, secure, and compliant deployment of AI technologies—including Agentic AI, Generative AI (GenAI), and traditional ML models—within hybrid cloud environments. The engineer will collaborate with AI architects, ML engineers, and platform teams to ensure high availability, performance, and governance of AI systems.

• 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.
• Monitor system health, usage, and performance using cloud-native observability tools.
• Work closely 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.

• 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 Dev Ops.
• 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