Agentic AI & Commerce Architect

Overview

As an Agentic AI & Commerce Architect, you design and deliver production-grade agentic commerce systems for global enterprises. You define overall system architecture, select AI/ML and platform technologies, and ensure scalable, secure solutions integrated with live commerce environments. You lead cross-functional collaboration across development, DevOps, and client teams to translate strategy into executable, production-ready architecture. This role sits at the intersection of enterprise commerce and agentic AI, offering impact at scale with meaningful governance and observability. You will shape standards, roadmaps, and engagement with C-suite stakeholders, driving measurable ROI.

Pay / Benefits

• competitive base salary
• annual performance bonus
• equity opportunities
• health and wellbeing benefits
• up to 30 days leave + volunteering days
• flexible work policies

Responsibilities

• Design multi-agent architecture blueprints and governance patterns
• Architect knowledge layer with embeddings, vector retrieval, and semantic search for commerce
• Lead integration with OMS, PIM, DAM, CRM, payments, and fulfillment via APIs and event buses
• Evaluate build vs buy across LLM platforms and orchestration frameworks
• Embed AI governance, observability, guardrails, and compliance into architecture
• Lead large-scale agentic commerce implementations with major platforms (Salesforce, Adobe, SAP, MACH)
• Define architectural runway, CI/CD-enabled scaling, and AgentOps/LLMOps framework
• Develop KPIs for agent performance, uplift, and ROI
• Shape architecture standards, deliverable accelerators, and client-ready assets
• Mentor and grow engineering talent within the practice

Key requirements

• 8+ years in AI/ML systems with production Generative AI experience
• 4+ years enterprise commerce delivery on Salesforce Commerce Cloud, Adobe Commerce, SAP Commerce, or MACH stacks
• Experience designing LLM-based systems including RAG, tool-calling, multi-agent orchestration
• Vector retrieval architectures and embedding pipelines in production
• AI governance frameworks with auditability, HITL, red teaming, compliance controls
• AgentOps/LLMOps: observability, tracing, model evaluation in production
• Commerce stack integration with OMS, PIM, DAM, CRM, payments, fulfillment
• Proficiency in Python, agent frameworks, vector databases, APIs/microservices, distributed systems
• Cloud delivery on AWS, GCP, or Azure; CI/CD and cloud-native architecture
• Demonstrated leadership of complex, multi-region enterprise programs

• Leadership across multidisciplinary teams
• Stakeholder and client workshops with senior executives
• Clear communication of complex trade-offs and roadmaps
• Python
• agent frameworks
• vector databases

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