Staff AI-Driven CI/CD Automation Engineer

Showcify, Inc.; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

d-Matrix is seeking a Staff-level software infrastructure contributor to own CI/CD automation across cloud and on-prem environments. You will drive diagnosing and fixing pipeline failures, including regression and infrastructure issues, while shaping architecture for scalable compute and storage.

Collaboration with Software Infrastructure, development groups, and QE is key. The role emphasizes blending AI techniques with deterministic automation to maximize reliability, with an expectation to

Qualifications

• Proven track record building automation that reduces toil or time-to-signal in CI/CD or dev tooling.
• Release engineering experience with versioning schemes and multi-component release trains.
• Architectural judgment on AI versus deterministic software and compute vs data locality.

Responsibilities

• Design and build automation that diagnoses and resolves CI/CD pipeline failures and classifies regressions and infrastructure issues.
• Develop automated methods to identify which merges cause failures in long-running test suites.
• Evaluate and integrate AI techniques alongside deterministic automation for reliability.
• Architect scalable compute and storage for build and test workloads across cloud and on-prem environments.
• Own release engineering practices, including versioning schemes, independent component release trains, and compatibility matrices.
• Reduce developer toil and time-to-signal across the product, dev, test, and release pipeline.
• Partner with development groups and Quality Engineering to drive adoption of new tooling and best practices.

Skills

CI/CD automation

AI integration

Kubernetes

Python

Automation engineering

Tools

GitLab CI

Job description

d-Matrix is seeking a Staff-level software infrastructure contributor to own CI/CD automation across cloud and on-prem environments. You will drive diagnosing and fixing pipeline failures, including regression and infrastructure issues, while shaping architecture for scalable compute and storage.

Collaboration with Software Infrastructure, development groups, and QE is key. The role emphasizes blending AI techniques with deterministic automation to maximize reliability, with an expectation to