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Senior AI Solutions Engineer - UAE

DataRobot•United Arab Emirates•🌍 Remote
Full-timeSenior
👁️ 0 views•📝 0 applications•Posted 10/2/2026•Expires 12/1/2026
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Job Description

: DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets.

Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future. The Pre-Sales Senior AI Solutions Engineer plays a pivotal role in helping enterprise customers see, feel, and believe in the value of agentic AI and ML platforms.

Sitting at the intersection of business strategy, AI application design, and polished execution, your primary mission is to rapidly build enterprise-grade MVP agentic AI applications.

You will partner with prospective customers and sales teams to map loosely defined problems into compelling, production‑inspired prototypes.

These MVPs serve as credible, extensible foundations that showcase technical depth and accelerate time-to-value, acting as the bridge between immediate problem-solving and long-term platform adoption.

Key Responsibilities

Business-to-Technical Translation & Problem Understanding Partner with Sales Teams: Understand customer missions, strategic priorities, and constraints through short discovery sessions.

Map Capabilities: Translate business needs into platform capabilities, tailoring messaging for different personas (CIO, CTO, Chief Data Officer, program leads, technical practitioners).

Identify Value: Pinpoint high-leverage automation and decision points where agentic AI can create immediate, visible value, translating ambiguous problems into clear user journeys and agent responsibilities.

Agentic AI Solution Design & Prototyping Rapid MVP Build: Design and implement end-to-end agentic AI MVPs, including multi-agent orchestration, tool use, memory, Model Context Protocol (MCP) servers, and agent observability. Deployment Readiness: Define key tech

Required Skills

AIMLMVPagentic AIprototypingmulti-agent orchestrationModel Context Protocolagent observabilitybusiness strategyAI application designtechnical depthautomationdecision pointsuser journeysdeployment readiness

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