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.
