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Emmanuel ChristopherEC
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Emmanuel Christopher

@emmanuelchristopher

I build secure, observable, cost-efficient cloud platforms for AI and data systems.

Nigeria
Message

What I'm looking for

I'm looking to build secure, observable, and cost-efficient cloud platforms for AI, data-heavy, and high-reliability systems, with ownership of infrastructure automation, deployment safety, compliance, and operational excellence.

At RestoreAI, I own cloud platform and DevOps operations across AWS, Nebius, Terraform/Terragrunt, GitHub Actions, PostgreSQL, observability, and GPU-backed AI workloads. I reduced dev and staging AWS spend from roughly $700/day to $200/day, hardened cloud posture, and led infrastructure-side SOC 2 readiness through automated evidence collection and compliance-as-code workflows.

Previously, I built low-latency APIs and real-time data services at GlueX Protocol, achieving under 250 ms p90 latency and reducing AWS costs by 45%. I also created KraiNode, a browser-based RPC diagnostics and benchmarking tool used by 400+ engineers globally.

Experience

Work history, roles, and key accomplishments

RG
Current

Cloud Platform / DevOps Architect

RestoreAI (by GhostDog)

Feb 2026 - Present (6 months)

Owned cloud platform, DevOps, and infrastructure operations end-to-end across AWS, Nebius, GitHub Actions, Terraform/Terragrunt, PostgreSQL, and GPU-backed workloads. Reduced dev/staging AWS spend from roughly $700/day to $200/day and led infrastructure-side SOC 2 readiness.

FC

Cloud Platform / DevOps Architect Consultant

Freelance / Independent Consultant

Sep 2025 - Feb 2026 (5 months)

Helped early-stage teams improve deployment workflows, cloud infrastructure, observability, and data infrastructure across self-hosted and managed environments. Built and maintained KraiNode, a browser-based RPC diagnostics tool used by 400+ engineers globally.

Education

Degrees, certifications, and relevant coursework

AA

ALTSCHOOL AFRICA

Diploma, Data Engineering

Diploma in Data Engineering from ALTSCHOOL AFRICA, where the candidate was a top-performing graduate.

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