AI-Driven Platform Engineer

Reejig; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Reejig is seeking a Delivery Engineer to make it fast, safe and reliable for enterprise-scale software. You will own cloud infrastructure, IaC, deployment workflows and security, with a bias toward automation and continuous improvement.

You will shape how AI is used in the engineering lifecycle, build AI-assisted workflows, and improve observability, reliability and cost. You will work across regions to keep the platform scalable and secure in a fast-moving SaaS environment.

Qualifications

• 5+ years in platform engineering, DevOps, SRE or similar with production responsibility.
• Strong experience with AWS or another major cloud platform and Terraform.
• Production experience with containerised workloads and modern deployment patterns.
• Experience designing and operating CI/CD pipelines and release processes.
• Hands-on experience with relational databases in production.
• Experience with observability, monitoring and alerting systems.
• Solid security fundamentals across identity, access, secrets, encryption and authentication.
• Experience reading and modifying service code in Python or Go.

Responsibilities

• Own and evolve cloud infrastructure and IaC across environments.
• Improve reliability, scalability and efficiency of the platform.
• Build and refine CI/CD and release workflows for fast, reversible shipping.
• Operate core data, networking and platform services.
• Develop AI-assisted engineering workflows to speed development while preserving quality.
• Create runbooks and documentation for the engineering team.

Skills

Platform engineering

DevOps

SRE

Python/Go

AI tooling

Tools

AWS

Terraform

CI/CD tooling

Observability tooling

Job description

Reejig is seeking a Delivery Engineer to make it fast, safe and reliable for enterprise-scale software. You will own cloud infrastructure, IaC, deployment workflows and security, with a bias toward automation and continuous improvement.

You will shape how AI is used in the engineering lifecycle, build AI-assisted workflows, and improve observability, reliability and cost. You will work across regions to keep the platform scalable and secure in a fast-moving SaaS environment.