• Build and scale a solutions engineering function to support sales and customer outcomes • Own executive relationships with key customer and internal stakeholders, with accountability for: • Contribute to a formal solutions engineering enablement and competency program • Contribute to the operating rhythm to manage and scale solutions engineering • Helping define product lines and GTM strategies for Remote build • Architect and implement AI agent workflows

• Build and scale a solutions engineering function to support sales and customer outcomes • Define role profiles and coverage model (segments, regions, product lines) • Establish a repeatable technical discovery and solution design process • Set clear engagement models, roles/responsibilities, and success metrics • Own executive relationships with key customer and internal stakeholders, with accountability for: • Commercial impact (deal support, win rates, cycle time reduction, revenue influence) • Technical quality (solution accuracy, implementation readiness, customer satisfaction, escalations, continuous improvement) • Alignment to product vision (AI adoption, roadmap inputs, standardization) • Contribute to a formal solutions engineering enablement and competency program • Define levels, requirements, and maintenance criteria (training, assessments, quality metrics) • Partner with Solution Architecture to codify technical standards, reference architectures, and best practices • Ensure competencies are measurable, auditable, and scalable • Contribute to the operating rhythm to manage and scale solutions engineering • Business reviews / performance reviews with Sales and key stakeholders • Clear escalation paths and incident learnings • Reporting on team health, coverage, and capability gaps • Helping define product lines and GTM strategies for Remote Build • Building ADRs and PRDs for potential products • Identifying and abstracting solution spaces • Putting AI at the forefront of everything we do • Architect and implement AI agent workflows • Translate business processes into agent-enabled workflows (intake, orchestration, guardrails, evaluation) • Prototype with modern LLM tooling and iterate toward production-grade implementations • Design human-in-the-loop patterns, escalation paths, and observability (quality, cost, latency) • Partner with Engineering and Product to ship secure, reliable agent capabilities (APIs, permissions, data access)

• Build and scale a solutions engineering function to support sales and customer outcomes • Define role profiles and coverage model (segments, regions, product lines) • Establish a repeatable technical discovery and solution design process • Set clear engagement models, roles/responsibilities, and success metrics • Own executive relationships with key customer and internal stakeholders, with accountability for: • Commercial impact (deal support, win rates, cycle time reduction, revenue influence) • Technical quality (solution accuracy, implementation readiness, customer satisfaction, escalations, continuous improvement) • Alignment to product vision (AI adoption, roadmap inputs, standardization) • Contribute to a formal solutions engineering enablement and competency program • Define levels, requirements, and maintenance criteria (training, assessments, quality metrics) • Partner with Solution Architecture to codify technical standards, reference architectures, and best practices • Ensure competencies are measurable, auditable, and scalable • Contribute to the operating rhythm to manage and scale solutions engineering • Business reviews / performance reviews with Sales and key stakeholders • Clear escalation paths and incident learnings • Reporting on team health, coverage, and capability gaps • Helping define product lines and GTM strategies for Remote build • Building ADRs and PRDs for potential products • Identifying and abstracting solution spaces • Putting AI at the forefront of everything we do • Architect and implement AI agent workflows • Translate business processes into agent-enabled workflows (intake, orchestration, guardrails, evaluation) • Prototype with modern LLM tooling and iterate toward production-grade implementations • Design human-in-the-loop patterns, escalation paths, and observability (quality, cost, latency) • Partner with Engineering and Product to ship secure, reliable agent capabilities (APIs, permissions, data access)

• 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.