AI Solution Engineer
AI Summary
Pre-Sales AI Solution Engineer designs, validates, and presents AI solutions for customer engagements, articulating architecture, data flows, and security considerations to support sales cycles.
About this role
As a Pre-Sales — AI Solution Engineer at Arabic.AI, you will design,validate, and present AI solutions that support sales cycles and customer decision-making. The role directly improves win-rate, deal velocity, and customer confidence by ensuring that proposed solutions are technically sound, secure, implementable, and aligned with real customer needs.
The AI Solution Engineer acts as the technical authority in the sales cycle—bridging customer requirements, product capabilities, and delivery feasibility while preventing over-promising and ensuring clean, executable handoffs to delivery teams.
Duties & Responsibilities
Technical Discovery & Solution Design
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Lead technical discovery sessions to understand customer requirements, constraints, and success criteria.
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Design AI solutions including architecture, data flows, integrations, and operational considerations.
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Assess feasibility, dependencies, risks, and assumptions early in the sales cycle.
Demos, Workshops & Customer Engagement
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Run demos, workshops, proof-of-concepts (PoCs), and executive-level technical sessions.
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Translate complex technical concepts into clear, value-driven narratives tailored to different stakeholders.
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Address technical objections and build customer confidence in solution viability.
Solution Validation & Deal Readiness
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Produce solution artifacts including architecture diagrams, security posture summaries, effort estimates, and success criteria.
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Validate scope, assumptions, and dependencies to prevent over-commitment.
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Ensure solutions meet internal technical, security, and delivery standards before close.
Delivery Handoff & Execution Alignment
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Ensure clean handoff to delivery teams with clearly defined scope, assumptions, and acceptance criteria.
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Support early delivery alignment to reduce rework, delays, and scope creep.
Asset Reuse & Capability Building
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Build and maintain reusable assets such as reference architectures, demo kits, templates, and solution playbooks.
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Contribute to continuous improvement of pre-sales tooling, documentation, and best practices.
Education, Experience & Qualifications
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Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field.
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3-5 years of experience in pre-sales, solution engineering, technical consulting, or AI/ML solution roles.
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Practical experience designing and presenting AI-driven solutions in enterprise environments.
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Solid understanding of AI/ML, LLMs, agentic workflows, APIs, and system integrations.
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Familiarity with security, compliance, and enterprise architecture considerations.
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Excellent written and verbal communication skills in English.
Behavioral Competencies
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Initiative
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Problem Solving
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Team Oriented
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Adaptability
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Ability to Work Under Pressure
Technical Competencies
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Solution Architecture & Integration Design
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AI / LLM & Agentic Workflow Understanding
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Security & Feasibility Assessment
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Technical Documentation & Diagramming
Skills
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