Job Title: GLEN AI Engineer/ GLEN AI Data Engineer
Location: Remote
Duration: 5-6 Months
JOB DESCRIPTION – GLEN AI Engineer/ GLEN AI Data Engineer
We are seeking an AI Architect & Engineer to design secure, scalable solutions across platforms such as Glean, StackAI, Snowflake, Salesforce (SFDC), and other enterprise technologies. This role will identify and prioritize high-value AI opportunities, evaluate use case-to-tool mapping, and translate business needs into governed architectures, integrations, knowledge experiences, agents, and workflow automation.
The ideal candidate can bridge strategy and implementation—assessing feasibility, value, risk, and operational readiness while partnering across business, data, security, compliance, and technology teams to move AI use cases from concept to production.
Key responsibilities
• Evaluate business use cases and map them to the right platforms, models, tools, and delivery patterns.
• Design secure, permission-aware, observable, and scalable AI architectures and workflows.
• Establish recommendations for governance, privacy, data classification, access management, security controls, auditability, and risk management.
• Evaluate AI vendors and solutions in regulated or compliance-sensitive environments.
• Facilitate cross-functional conversations and turn ambiguous needs into clear recommendations and executable next steps.
Required qualifications
• Experience developing AI strategy and/or architecting enterprise AI, search, knowledge-management, or workflow-automation solutions.
• Hands-on experience with platforms such as Glean, StackAI, or comparable enterprise AI technologies.
• Strong understanding of AI governance, security controls, privacy, compliance, auditability, and controlled change management.
• Experience working in regulated or compliance-sensitive industries.
• Excellent communication, facilitation, and stakeholder-management skills.
Nice to have
• Experience with Snowflake, Salesforce (SFDC), enterprise data integration, APIs, and related security models.
• Experience taking AI use cases from pilot through production, including measurement, monitoring, and adoption.
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