AI Solutions Architect
About the role
Overview
Instacart's Enterprise Solutions team is building a first-of-its-kind business: embedding directly with enterprise retail and CPG partners to design, sell, and deliver AI-powered solutions at scale. We are a small, senior, field-first pod—part startup, part consultancy—defining the playbook as we go.
As the AI Solutions Architect, you own the data and AI architecture, integration design, and governance across every engagement the pod runs. You are the person who makes Instacart's Intelligence Platform actually work inside real partner environments. This is a hands-on, field-first role—you will embed with partner engineering teams to map data ontologies, design integrations, and co-build solutions that work in the real world, not just on a whiteboard.
About the Job
- Own data modeling, integration design, and governance across every engagement; serve as the senior technical authority from pre-sales through delivery.
- Map customer data and Instacart's data ontology together, and gate technical feasibility before any build begins.
- Establish integration patterns between the Intelligence Platform and partner systems, e.g., POS, ERP, loyalty, CRM, Snowflake, proprietary APIs, and mobile surfaces.
- Bridge partner technical requirements with Instacart R&D roadmaps, APIs, and SDKs; surface gaps and advocate for platform changes needed to serve the field.
- Prototype and code in real-time alongside partners.
- Review designs and unblock the Forward Deployed Engineers to ensure architectural integrity across the pod's engagements.
- Codify reusable integration patterns into scalable architecture templates as the pod scales.
We are looking for someone energized by ambiguity, who builds for reuse and can navigate both a partner's technical reality and Instacart's platform constraints simultaneously, finding the optimal path between them.
About You
Minimum Qualifications
- 10+ years in solutions architecture, data engineering, or senior software engineering, with demonstrated experience designing enterprise-scale systems.
- Deep expertise in data architecture and modeling across messy, heterogeneous enterprise environments, with enough AI/ML familiarity to understand how data quality and structure determine what is possible on the intelligence layer.
- Experience designing integrations across complex enterprise environments including ERP, POS, Snowflake, and proprietary APIs.
- Hands-on coding is non-negotiable — the ability to build is as important as the ability to design.
- Proven customer-facing experience.