Devops Engineer

ASCENDING
12hOnsite

About The Position

We are looking for a highly skilled AWS DevOps Engineer with a strong background in AWS Solution Architecture to join our team in Fairfax. This role is unique in its focus on integrating cutting-edge AI technologies, specifically Amazon Bedrock, into our cloud-native infrastructure. You will be responsible for designing, automating, and maintaining robust CI/CD pipelines while ensuring our cloud networking and AI services are architected for scale, security, and performance.

Requirements

  • 5–7 years of professional experience in DevOps, Cloud Engineering, or Solution Architecture.
  • Proven experience as an AWS Solution Architect (Certification preferred) with a deep understanding of core services (EC2, S3, Lambda, RDS, IAM).
  • Direct experience supporting and configuring Amazon Bedrock.
  • Strong hands-on experience with Cloud Networking architecture and troubleshooting.
  • Expert knowledge of Terraform, Jenkins/GitLab CI, and containerization (Docker/Kubernetes).
  • Ability to work onsite 5 days a week in Fairfax, VA.

Nice To Haves

  • Familiarity with Azure OpenAI Service and hybrid-cloud AI implementations.
  • AWS Certified Solutions Architect – Professional or AWS Certified DevOps Engineer – Professional.
  • Advanced proficiency in Python, Bash, or Go for infrastructure automation.

Responsibilities

  • AWS Solution Architecture: Design and implement scalable, resilient, and secure cloud solutions following AWS Well-Architected Framework principles.
  • Automation & IaC: Build and maintain Infrastructure as Code (IaC) using Terraform or CloudFormation to manage multi-account AWS environments.
  • CI/CD Pipelines: Develop and optimize automated deployment pipelines to support rapid software delivery cycles.
  • Cloud Networking: Architect and manage complex cloud networking components, including VPCs, Transit Gateways, Direct Connect, and VPN configurations.
  • Amazon Bedrock Support: Manage and optimize Amazon Bedrock environments, including model deployments, provisioning, and integration with existing applications.
  • LLM Ops: Implement monitoring and logging for GenAI workloads to ensure high availability and cost-efficiency.
  • Cross-Cloud Integration: (Preferred) Support or collaborate on initiatives involving Azure OpenAI Service where cross-platform AI integration is required.
  • Ensure all cloud infrastructure meets rigorous security standards and best practices.
  • Provide high-level technical support for complex infrastructure and connectivity issues.
  • Collaborate with development teams to promote a culture of DevOps and cloud-native architecture.
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