Sr. Cloud Engineer - AI Infrastructure

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., Cloud Architecture & Infrastructure

· 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.

AI Platform Enablement

· 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.

Security & Compliance

· 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.

Automation & DevOps

· 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.

Collaboration & Support

· 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 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.

Pulled from the full job description

• 401(k)
• Health insurance
• Paid time off, * 401(k)
• Health insurance
• Paid time off