AI Solutions Engineer (Supply Chain AI & Automation)

Key Responsibilities (Written as measurable delivery)

1) Discovery & Value Definition

• Facilitate workshops with Operations, Planning, Logistics, Finance, and IT to map processes and identify automation opportunities.
• Convert ambiguous pain points into concrete artifacts:
• problem statements, SIPOC, requirements, risk assumptions
• data readiness assessment
• measurable success metrics (baseline vs target)

2) Roadmap + Business Case Ownership

• Build and maintain a 1–3 year roadmap of AI initiatives with sequencing, dependencies, and resourcing needs.
• Create business cases using financial justification (ROI, payback, sensitivity ranges) and operational baselines.

3) Build & Deploy AI Solutions (Hands-On)

• Develop production-grade AI solutions and agents using modern AI technologies, including LLM APIs where appropriate.
• Implement evaluation + monitoring to ensure accuracy, stability, and safety in real workflows.
• Deploy solutions in a way that is supportable, auditable, and measurable.

4) Technology Stewardship & Enablement

• Define best practices for prompt design, agent tools, safe data usage, and responsible AI patterns.
• Document solutions (runbooks, user guides, change logs) and train business users to adopt and maintain solutions.

5) KPI Tracking & Continuous Improvement

• Measure savings and performance: time saved, error reduction, throughput impact, service improvements.
• Iterate based on telemetry, user feedback, and operational changes.