Senior Infrastructure Engineer (17776)

Project overview

Baer is looking for Senior Infrastructure Engineer for a 9-month Federal Project located in Woodlawn, MD Title: Senior Infrastructure Engineer

Our client is looking for an experienced Senior Infrastructure Engineer to design, build, secure, and operate scalable multi-cloud infrastructure across AWS and Azure. The role focuses on Kubernetes platforms (AWS EKS and Azure AKS), Infrastructure as Code (IaC), CI/CD and GitOps automation, cloud networking, observability, and AI/LLM application telemetry. The ideal candidate will have strong hands-on cloud engineering expertise and a proven ability to deliver secure, resilient, and production-ready infrastructure.

Description:

Baer provides best-in-class engagement experiences for our consultants. Our job requirements are carefully vetted and are typically associated with pivotal programs offering tremendous opportunities to expand your skills leveraging the latest solutions. Baer is an equal opportunity employer including disability/veteran.

Job Facts: Contract W2 | Contract Independent | 9 Months | Hybrid | Depends on Experience

Skills: AWS & Azure Cloud Engineering, Kubernetes/Docker & Helm, Infrastructure as Code (CloudFormation/CDK), GitOps/ArgoCD & CI/CD Automation, Cloud Monitoring/Security & AI Observability

Reference: Dice Id: baerga | Position Id: 9125411

• Design, deploy, scale, and manage production Kubernetes clusters using AWS EKS and Azure AKS.
• Build secure, highly available multi-cloud architectures, including networking, IAM, storage, secrets, and compute resources.
• Develop reusable Infrastructure as Code modules using AWS CloudFormation and AWS CDK (TypeScript/Python).
• Implement CI/CD and GitOps workflows using Jenkins, ArgoCD, Helm, Docker, and Nexus.
• Manage AWS services, including ECR, RDS (PostgreSQL/Aurora), Secrets Manager, IAM, EC2, and CloudTrail.
• Configure Azure services, including APIM, Azure OpenAI/Foundry pipelines, Azure Monitor, Entra ID, and Azure VMs.
• Design cloud networking solutions using VPCs, subnets, CNI networking, ingress controllers, and load balancers.
• Implement container build pipelines with integrated security scanning and artifact lifecycle management.
• Configure and maintain observability solutions using Dynatrace, Splunk, Azure Monitor, and Log Analytics.
• Build dashboards and alerts for infrastructure health, Kubernetes performance, applications, APIs, and AI/LLM latency, traces, and errors.
• Deploy and manage LangSmith or LangFuse on Kubernetes to support AI application tracing, evaluation, and telemetry.
• Troubleshoot complex infrastructure, deployment, networking, performance, and reliability issues while maintaining security and operational best practices.

Requirements

Public Trust Security Clearance is the lowest level of additional background screening that the federal government requires for applicants of certain jobs, which includes completing a form.

• 5+ years of cloud engineering experience, with strong hands-on experience designing and operating production infrastructure.
• Strong expertise in AWS EKS and Azure AKS, including cluster design, scaling, networking, security, and operations.
• Proficiency in AWS services: ECR, RDS (PostgreSQL/Aurora), Secrets Manager, IAM, EC2, and CloudTrail.
• Proficiency in Azure services: APIM, Azure OpenAI/Foundry pipelines, Azure Monitor, Entra ID, and Azure VMs.
• Strong knowledge of multi-cloud architecture, cloud networking, Kubernetes, Docker, Helm, and production troubleshooting.
• Hands-on experience with AWS CloudFormation and AWS CDK using TypeScript or Python.
• Strong experience with ArgoCD, Jenkins (Groovy pipelines), GitOps, and CI/CD automation.
• Experience building reusable IaC modules for networking, IAM, Kubernetes clusters, storage, secrets, and automation pipelines.
• Hands-on experience with Nexus artifact management and container image security scanning.
• Experience configuring Dynatrace, Splunk, Azure Monitor, and Log Analytics for monitoring, logging, dashboards, and alerting.
• Understanding of AI/LLM observability, including prompt tracing, model latency, distributed traces, error monitoring, and evaluation.
• Experience deploying and managing LangSmith or LangFuse in Kubernetes environments.
• Strong analytical, troubleshooting, documentation, communication, and cross-functional collaboration skills.
• Bachelor s Degree.

Project details

Hybrid - Woodlawn, MD (Local Required)

9 months

All-inclusive

Alignment: W2 or C2C

• Start: flexible
• Duration: 9 Months
• Remote: hybrid
• Location: Woodlawn, MD, US, US