AI Solutions Architect
New
Based in the United StatesFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 10+ years
- Required Skills
- SnowflakeData engineeringCRMData modeling
Requirements
- 10+ years of experience in solutions architecture, data engineering, or senior software engineering roles.
- Strong expertise in enterprise-scale data architecture, modeling, and system design in complex environments.
- Hands-on coding ability with the capacity to build, prototype, and troubleshoot production-grade systems.
- Proven experience designing integrations across enterprise platforms such as ERP, POS, Snowflake, CRM, and APIs.
- Deep systems thinking with the ability to manage both high-level architecture and detailed implementation work.
- Experience presenting technical solutions to both engineering teams and executive stakeholders.
- Ability to operate effectively in ambiguous, greenfield environments and define architecture from first principles.
- Familiarity with AI/ML concepts and how data structure impacts intelligence layer performance.
- Experience in retail tech, e-commerce infrastructure, or high-growth enterprise environments is a strong plus.
Responsibilities
- Own end-to-end data modeling, AI architecture, and integration design across enterprise partner engagements.
- Serve as the senior technical authority from pre-sales through delivery, ensuring architectural feasibility and integrity.
- Design and implement integration patterns across enterprise systems such as ERP, POS, CRM, Snowflake, and proprietary APIs.
- Map and reconcile partner data structures with platform ontologies to enable scalable AI-driven solutions.
- Prototype, code, and validate technical solutions in real time alongside partner engineering teams.
- Act as a bridge between customer requirements and internal product/R&D teams, influencing platform evolution where needed.
- Review technical designs and unblock delivery teams to ensure consistent architectural standards across engagements.
- Define reusable frameworks, templates, and integration patterns to scale delivery across multiple clients.
- Ensure governance, security, and performance considerations are embedded in all architectural decisions.
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