Devops Engineer

ASCENDING

8h•Onsite

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.