AI Solutions Architect

Instacart Instacart · Consumer · United States · Remote · Professional Services

Instacart's Enterprise Solutions team is seeking an AI Solutions Architect to own the data and AI architecture, integration design, and governance for AI-powered solutions embedded with enterprise retail and CPG partners. This hands-on role involves mapping data ontologies, designing integrations with partner systems (POS, ERP, loyalty, CRM), prototyping, and codifying reusable patterns. The role requires strong systems thinking, deep expertise in data architecture, and the ability to code alongside partners.

What you'd actually do

  1. Own data modeling, integration design, and governance across every engagement; serve as the senior technical authority from pre-sales through delivery.
  2. Map customer data and Instacart's data ontology together, and gate technical feasibility before any build begins.
  3. Establish integration patterns between the Intelligence Platform and partner systems, e.g.,POS, ERP, loyalty, CRM, Snowflake, proprietary APIs, and mobile surfaces.
  4. Bridge partner technical requirements with Instacart R&D roadmaps, APIs, and SDKs; surface gaps and advocate for platform changes needed to serve the field.
  5. Prototype and code in real-time alongside partners

Skills

Required

  • 10+ years in solutions architecture, data engineering, or senior software engineering
  • Demonstrated experience designing enterprise-scale systems
  • Deep expertise in data architecture and modeling across messy, heterogeneous enterprise environments
  • Experience designing integrations across complex enterprise environments including ERP, POS, Snowflake, and proprietary APIs
  • Proven customer-facing experience presenting technical architectures to both engineering and executive audiences
  • Strong systems thinking
  • Ability to code

Nice to have

  • Background in retail tech, e-commerce infrastructure, or CPG data systems (POS, ERP,, Snowflake)
  • Familiarity with open agent standards or multi-agent orchestration frameworks
  • Prior experience in enterprise software implementation or systems integration
  • Startup or high-growth environment experience
  • AI/ML familiarity to understand how data quality and structure determine what is possible on the intelligence layer

What the JD emphasized

  • Hands-on coding is non-negotiable
  • Comfort defining architecture from first principles in greenfield, ambiguous environments

Other signals

  • Owns data and AI architecture, integration design, and governance
  • Embeds with partner engineering teams to map data ontologies, design integrations, and co-build solutions
  • Prototypes and codes in real-time alongside partners
  • Codifies reusable integration patterns into scalable architecture templates