Senior Customer Solutions Architect (AI Readiness & Enterprise Data)
New
H
Hire HangarTech, SaaS, AI
South Africa - Cape Town, Cuba - Havana, Chile - Santiago, South Africa - Johannesburg, Haiti - Port-au-Prince, Peru - Lima, Dominican Republic - Santo Domingo, Nicaragua - Managua, Argentina - Buenos Aires, Panama - Panama City, Mexico - Mexico City, US Time Zones (EST–PST)ContractSenior
Salary2,000 - 3,000 USD per month
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonCloud ComputingTerraform
Requirements
- 5+ years in a customer-facing architecture or solutions role (Solutions Architect, Solutions Engineer, Sales Engineer, Customer-Facing Systems Engineer) within Tech, SaaS, or AI environments.
- Strong understanding of enterprise infrastructure across hybrid/on-prem and cloud environments, including data movement and integration patterns.
- Practical knowledge of security and IAM concepts, access models, and governance/compliance considerations.
- Proven ability to lead technical discovery, communicate architectural trade-offs, and present to mixed technical and executive audiences.
- Comfortable working hands-on within customer environments to implement and validate POV deployments.
- AI literacy, including understanding AI readiness requirements and how data quality and governance impact AI outcomes.
- Prior remote work experience and fluency with remote collaboration tools/platforms (Slack, Zoom, Google Workspace, Asana, or similar).
- Must have ideally worked with US or UK-based companies.
Responsibilities
- Partner with Sales to lead technical discovery and define clear POV success criteria.
- Assess enterprise environments (on-prem, cloud, hybrid), including storage, file systems, IAM, security, and compliance requirements.
- Design solution architectures supporting unstructured data scanning, classification, and AI-ready data preparation.
- Deliver tailored demos and technical presentations to architects, security teams, and business stakeholders.
- Lead end-to-end POV execution: installation, configuration, integrations, and outcome validation.
- Troubleshoot deployment and performance issues while validating measurable value.
- Support transition to production through documentation, internal handoff, and identification of expansion opportunities.
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