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Senior Infrastructure Engineer

Job

SGS Consulting

San Jose, CA (In Person)

Full-Time

Posted 3 days ago (Updated 23 hours ago) • Actively hiring

Expires 7/23/2026

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Job Description

Senior Infrastructure Engineer at SGS Consulting Senior Infrastructure Engineer at SGS Consulting in San Jose, California Posted in about 4 hours ago.
Type:
full-time
Job Description:
Years of Experience :
8-10 years (Level IV) | 12 Months W2
Contract Role Job Description:
Build and operate the software/infrastructure backbone of the AI Factory tooling - dashboard, data pipeline, and image-inspection pipeline - on production-grade Client infrastructure. (Same scope as our current dashboard/infra owner.)
Responsibilities:
Build and maintain the AI Factory dashboard and the yield/triage data pipeline (ingest, scheduled processing, uptime).
Support the image-inspection pipeline:
factory image ingestion and automated end-to-end processing. Operate on production-grade infra (Tupperware, S3) -- deployments, monitoring, on-call reliability. Onboard new factories onto the platform and scale capacity as we expand. Partner with factory-side engineers on camera/AOI and station-data integration.
Required:
Strong full stack / infrastructure software engineering. Data pipelines, cloud storage, and service deployment (S3, containerized services). Track record owning reliability / infra for a production tool, including scaling to new sites.
Nice-to-have:
Image/vision pipeline; manufacturing/factory data; Python + ML tooling; web dashboard / front-end experience.
Day-to-Day Responsibilities:
Maintain and harden the AI Factory dashboard and data pipeline (ingest, scheduled processing, uptime/stability). Support the image-inspection pipeline (factory image ingestion and automated processing end-to-end). Operate on production-grade infra (Tupperware, S3) with deployments, monitoring, and on-call stability. Partner with factory-side engineers on camera/AOI and station-data integration.
Must-Have HARD Skills:
Strong software / firmware engineering with data-pipeline experience. Cloud storage and service deployment (e.g., S3, containerized services). Track record owning reliability / infrastructure for a production tool.
Nice-to-have Skills:
Image / vision pipeline experience. Familiarity with factory / manufacturing data. Python and ML tooling.
Degrees/Certifications Required :
BS in Computer Science, EE, or equivalent.
Interview :
2 - 3 Rounds | Behavioral plus technical / system-design (data pipelines, service deployment, reliability) | 40 - 60 Minutes | A system they built and operated in production: architecture, data pipeline, deployment, and how they ensured reliability.