AI Solutions Architect

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

Instacart's Enterprise Solutions team is building a business embedding AI-powered solutions with enterprise retail and CPG partners. The AI Solutions Architect owns the data and AI architecture, integration design, and governance, embedding with partner engineering teams to design and co-build solutions. This role requires hands-on coding, mapping partner data to Instacart's ontology, establishing integration patterns, and advocating for platform changes.

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
  • Hands-on coding ability
  • Proven customer-facing experience presenting technical architectures
  • Strong systems thinking

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

What the JD emphasized

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

Other signals

  • embedding AI solutions with enterprise partners
  • owns data and AI architecture, integration design, and governance
  • hands-on, field-first role embedding with partner engineering teams
  • codify reusable integration patterns into scalable architecture templates