AI First Engineer – SCM Planning
Listed on 2026-09-27
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Software Development
AI Engineer (Applied/Software), AI QA / Validation Engineer
Job Summary
We are seeking an AI First Engineer with deep SCM expertise and a proven track record of applying AI across the entire Software Development Lifecycle SDLC This role is focused on transforming how Supply Chain applications are designed developed tested deployed and supported through AI enabled engineering practices
ResponsibilitiesWe are seeking an AIFirst Engineer with deep SCM expertise and a proven track record of applying AI across the entire Software Development Lifecycle SDLC This role is focused on transforming how Supply Chain applications are designed developed tested deployed and supported through AIenabled engineering practices
The ideal candidate is not simply a developer who occasionally uses AI tools but an engineer who consistently leverages AI technologies to improve productivity code quality testing efficiency operational support and overall software delivery outcomes
The role will drive AIpowered development and modernization initiatives with an SCM background particularly in planning
Candidates should be able to demonstrate and quantify measurable business outcomes achieved through AI adoption including reduced development cycle times improved code quality lower testing effort accelerated deployments and faster issue resolution
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Key Responsibilities- 1 AIAssisted Requirements Solution Design
Leverage AI and LLM technologies to analyze business requirements BRDs user stories process flows and SCM functional specifications
Generate technical designs impact assessments traceability matrices solution alternatives and effort estimates using AI assisted workflows
Utilize AI to accelerate fitgap analysis and quarterly upgrade impact assessments
Apply AIdriven knowledge discovery to reduce analysis and design cycle times
- 2 AIdriven code generation and refactoring
Use Git Hub Copilot Agentic AI frameworks and similar tools to accelerate development across PLSQL Java JavaScript Groovy VBCS OIC and APEX
Implement AI assisted code generation code optimization refactoring reverse engineering and legacy modernization initiatives
Develop SCM customizations integrations extensions reports and automation solutions using AIenabled development practices
Apply AI to automate integration mappings API creation report generation and technical documentation
- 3 AI assisted testing test automation and regression strategies
Build AIpowered testing strategies covering functional integration regression performance and user acceptance testing
Utilize AI for automated test case generation test data creation defect identification and test maintenance
Implement AIenhanced regression testing frameworks
Leverage AI tools for defect triage root cause analysis and predictive quality insights
- 4 AIenabled Dev Ops code review documentation generation and operational support
Integrate AI assisted code reviews security analysis static code scanning and quality gates into CICD pipelines
Utilize AI to generate deployment documentation release notes implementation guides and operational runbooks
Support AIdriven deployment automation and environment management practices
- 5
Experience with Git Hub Copilot Agentic AI frameworks prompt engineering RAG patterns and AI assisted developer workflowsGit Hub Copilot
ChatGPT
Claude
Agentic AI frameworks
OCI Generative AI
Ability to quantify and communicate outcomes from AI adoption including
- Development cycle time reduction
- Improved code quality
- Reduced defect rates
- Reduced testing effort
- Faster deployment cycles
- Faster incident resolution
- Increased developer productivity
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