Principal Software Engineer — AI-Driven AWS Cost Optimization

Infor

Atlanta (GA)

On-site

USD 180,000 - 230,000

Full time

14 days+

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Job summary

Infor is seeking a Principal Software Engineer to develop AI-driven tooling that optimizes AWS spend across our development and product estate. You will build software integrated into the SDLC to prevent cost overruns, while partnering with the FinOps team and platform squads to implement centralized controls.

The role emphasizes hands-on engineering, design leadership, and execution across many engineering teams.

Qualifications

  • Proven software engineer with production systems experience.
  • Expertise in at least one modern language used for tooling (Python/Java/Go).
  • Deep AWS experience including Cost Explorer, billing tools, IAM, Lambda, tagging.

Responsibilities

  • Design and build AI tooling to monitor, forecast, and auto-resolve cloud costs across AWS accounts.
  • Integrate cost guardrails into SDLC and CI/CD pipelines to catch overruns at commit/build/deploy.
  • Develop detection-to-remediation loops: anomaly detection, root-cause attribution, automated actions.
  • Instrument workloads for cost attribution and surface findings in dashboards.
  • Partner with hundreds of engineering organizations to embed cost tooling that speeds delivery timelines.
  • Collaborate with FinOps and platform teams on centralized controls and budget gateways.
  • Act as technical project lead: shape roadmap and drive cross-team work to completion.

Skills

Python/Java/Go
AWS
CI/CD pipelines
Data-driven decisions
Cross-team leadership

Tools

Cost Explorer
IAM
CloudFormation
Terraform

Job description

Infor is seeking a Principal Software Engineer to develop AI-driven tooling that optimizes AWS spend across our development and product estate. You will build software integrated into the SDLC to prevent cost overruns, while partnering with the FinOps team and platform squads to implement centralized controls.

The role emphasizes hands-on engineering, design leadership, and execution across many engineering teams.

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