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Forward Deployed Infrastructure Engineer
Tribe AIInfrastructure Engineer deploying AI systems in client infrastructures. Navigating enterprise constraints and debugging production systems in a variety of environments.
Posted 5/6/2026full-timeRemote • 🇺🇸 United StatesMid-LevelSenior💰 $200,000 - $300,000 per yearWebsite
Tech Stack
Tools & technologiesAWSAzureCloudDNSGoogle Cloud PlatformKubernetes
About the role
Key responsibilities & impact- Get AI systems running inside client infrastructure — cloud, containers, CI/CD.
- Navigate enterprise constraints: production readiness reviews, governance gates.
- Debug what breaks in production: networking, DNS, connection pooling.
- Set up observability, cost controls, and deployment pipelines.
- Own the technical relationship with the client's IT, Infrastructure, and DevOps counterparts.
- Get things done inside organizations where you control nothing and depend on everyone.
Requirements
What you’ll need- Expert-level in at least one cloud platform — AWS, GCP, or Azure.
- Strong hands-on experience with Kubernetes in production environments.
- Productionized data science outputs, deployed ML models, or run AI applications at scale.
- Deep production debugging experience: networking, DNS, latency, connection pooling.
- Managed technical relationships directly with client IT or DevOps counterparts.
- Background reads: production engineer, systems engineer, SRE, or platform engineer.
Benefits
Comp & perks- Impact: Ship AI systems that don’t just demo well but run at scale in Fortune 500 enterprises.
- Growth: Stay hands-on with cutting-edge frameworks while developing field-tested instincts.
- Variety: Solve problems across industries, from finance to healthcare to defense.
- Culture: Work in a team that prizes resilience, creativity, and winning over process.
- Trajectory: Build both your technical and consulting muscles in one of the most demanding roles in AI delivery.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
cloud computingKubernetesAI applicationsML modelsproduction debuggingnetworkingDNSconnection poolingCI/CDobservability
Soft Skills
relationship managementorganizational skillsproblem-solvingcollaborationcommunication