As a Principal AI Architect, you will define and govern the end-to-end technical architecture of Makkook’s Optimization & Decision Intelligence platform(s), and ensure we can deliver new customer implementations fast (target: ≤ 8 weeks per use case after core platform maturity).

Core Responsibilities:

Platform Architecture & Technical Strategy

Define platform architecture: modular components, data contracts, integration patterns, deployment topology (cloud/on-prem), and security/observability standards.

Design reusable “platform primitives”: canonical entities (resources/tasks/time/cost), constraint packs, objective templates, scenario manager, and explainability layer.

Make solver/stack decisions (build vs buy), and establish technical roadmaps with the CTO.

Optimization & Decision Engine Leadership

Lead modeling and solution strategy for key families:

Production planning & scheduling (sequence-dependent setups/changeovers, minimum run lengths, maintenance windows)

Workforce allocation and shift planning

Routing, dispatching, and fleet assignment

Inventory/replenishment and supply chain planning

Set standards for model formulation, performance, scalability, and stability (runtime budgets, warm starts, decomposition, heuristics/hybrids where needed).

Build a repeatable benchmarking harness and KPI framework (cost, service, risk, feasibility rate, runtime).

Feasibility, Diagnostics & Explainability

Own the approach to infeasibility detection and repair (constraint relaxation strategies, IIS where applicable, actionable diagnostics).

Ensure decisions are explainable to operations teams (constraints hit, trade-offs, what changed vs previous plan, reason codes).

Delivery & Engineering Excellence

Partner with PM/Delivery to define scope, milestones, acceptance criteria, and technical risk management.

Guide integrations with ERP/WMS/TMS/CMMS/SCADA and production data pipelines.

Establish OptOps practices: versioning, monitoring, runtime regressions, rollback, and quality gates.

Technical Leadership

Mentor AI engineers (including those coming from NLP/CV backgrounds) into OR/Optimization craftsmanship.

Run architecture reviews, ADRs, and enforce best practices across code, models, and deployments.