AI Solution Architect

Booz Allen HamiltonSan Diego, CA
2d$99,000 - $225,000

About The Position

AI Solution Architect The Opportunity: Serve as part of a platform engineering team responsible for enabling AI/ML workloads through the design and operation of cloud-native infrastructure. Build and maintain secure, scalable Kubernetes-based platform environments deployed in AWS, and develop Infrastructure-as-Code and automation frameworks to support scalable and repeatable infrastructure deployments. Implement CI/CD pipelines and Git-based workflows to support automated platform and application delivery, including Kubernetes deployment workflows and GitOps best-practices. Collaborate closely with data scientists, ML engineers, and application teams to support model training, experimentation, and deployment environments running on Kubernetes. Apply DevOps and platform engineering principles to improve reliability, automation, and operational efficiency. Identify and address gaps in infrastructure performance, bottlenecks, or scalability challenges, ensuring continual improvement of platform ecosystems. Implement monitoring, logging, and observability capabilities to support production systems and distributed workloads. Develop solutions to complex technical problems while providing general mentorship and guidance to junior team members as needed. Work independently with some guidance and review or guide activities of more junior employees.

Requirements

  • 5+ years of experience supporting cloud-native platforms, infrastructure engineering, or DevOps environments
  • 3+ years of experience operating and troubleshooting production Kubernetes clusters, including networking, storage, and workload management
  • Experience operating distributed systems or cloud-native platforms supporting large-scale applications or data workloads
  • Experience building and maintaining reusable Infrastructure-as-Code modules to provision and manage cloud infrastructure
  • Experience developing automation and scripting solutions using languages such as Python or Bash
  • Experience implementing CI/CD pipelines and Git-based workflows, including GitHub, Gitlab, Jenkins, or Helm
  • Experience implementing monitoring, logging, and observability solutions using tools such as CloudWatch, Grafana, or Elasticsearch
  • Secret clearance
  • Bachelor's degree

Nice To Haves

  • Experience supporting AI/ML platforms or ML infrastructure
  • Experience supporting data pipelines or workflow orchestration platforms
  • Experience supporting secure cloud environments or regulated systems
  • Experience supporting DoD or government cloud environments
  • Information Security Certification such as Security+ or CISSP Certification

Responsibilities

  • Serve as part of a platform engineering team responsible for enabling AI/ML workloads through the design and operation of cloud-native infrastructure.
  • Build and maintain secure, scalable Kubernetes-based platform environments deployed in AWS, and develop Infrastructure-as-Code and automation frameworks to support scalable and repeatable infrastructure deployments.
  • Implement CI/CD pipelines and Git-based workflows to support automated platform and application delivery, including Kubernetes deployment workflows and GitOps best-practices.
  • Collaborate closely with data scientists, ML engineers, and application teams to support model training, experimentation, and deployment environments running on Kubernetes.
  • Apply DevOps and platform engineering principles to improve reliability, automation, and operational efficiency.
  • Identify and address gaps in infrastructure performance, bottlenecks, or scalability challenges, ensuring continual improvement of platform ecosystems.
  • Implement monitoring, logging, and observability capabilities to support production systems and distributed workloads.
  • Develop solutions to complex technical problems while providing general mentorship and guidance to junior team members as needed.

Benefits

  • health
  • life
  • disability
  • financial
  • retirement benefits
  • paid leave
  • professional development
  • tuition assistance
  • work-life programs
  • dependent care
  • recognition awards program
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