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Senior Solutions Engineer – AI Data, Unstructured Data Platforms
Hire Hangar GlobalSenior Solutions Engineer managing technical customer journeys for AI data platforms. Collaborating with enterprise customers on scalable solutions across on-prem and cloud environments.
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing scalable solution architectures for enterprise customers, with a strong focus on AI readiness, governance, and compliance. Proficient in delivering technical presentations and managing end-to-end proof-of-value engagements in cloud and hybrid environments.
Highest-signal resume keywords
Enterprise Infrastructure ExperienceCloud/Hybrid Environments (AWS, Azure, GCP)Networking and Security FundamentalsAI Concepts and WorkflowsRemote Collaboration Tools Proficiency
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Solution ArchitectureDeployment Architecture DesignTechnical TroubleshootingIntegration and ValidationData PreparationGovernance ConsiderationsPerformance MeasurementPhased Rollout StrategiesTechnical DocumentationCustomer Engagement
Soft Skills
Clear CommunicationStakeholder EngagementFeedback Provision
Tools & Technologies
AWSAzureGCPSlackZoomGoogle WorkspaceAsana
Industry Keywords
AI ReadinessComplianceCost/Risk ManagementUnstructured Data EnvironmentsRemote Work Experience
Tech Stack
Tools & technologiesAWSAzureCloudFirewallsGoogle Cloud Platform
About the role
Key responsibilities & impact- Lead technical discovery with enterprise customers; translate business objectives (AI readiness, governance, compliance, cost/risk) into scalable solution architectures
- Deliver live demos, technical deep dives, and executive-level presentations tailored to diverse stakeholders
- Design and document deployment architectures across on-prem, cloud, and hybrid environments, outlining trade-offs and phased rollout strategies
- Own end-to-end proof-of-value engagements, including installation, configuration, integration, validation, and outcome measurement
- Troubleshoot deployment and performance issues; validate throughput, accuracy, and measurable business impact
- Drive transition from POV to production through documentation, knowledge transfer, and expansion planning
- Act as the technical voice of the customer, providing structured feedback to Product and Engineering teams
Requirements
What you’ll need- Experience in a customer-facing technical role (Solutions Engineer, Solutions Architect, Sales Engineer, Systems Engineer) within Tech, SaaS, or AI environments
- Strong experience with enterprise infrastructure across on-prem and cloud/hybrid environments (AWS, Azure, GCP)
- Solid foundation in networking and security fundamentals, including routing, firewalls, access controls, and IAM concepts
- Experience working with unstructured data environments (file systems, storage platforms, access models, governance considerations)
- Ability to communicate complex technical concepts clearly to both technical teams and executive-level stakeholders
- Working knowledge of AI concepts and practical familiarity with AI workflows, data preparation, and governance considerations
- Non-negotiable: Prior remote work experience and fluency with remote collaboration tools/platforms (Slack, Zoom, Google Workspace, Asana, or similar).
Benefits
Comp & perks- Health insurance
- Competitive pay
- Remote work opportunities