Job Overview
Location
Remote Dubai
Job Type
Full-time
Category
Engineering Manager
Date Posted
May 15, 2026
Full Job Description
đź“‹ Description
- • Lead end-to-end delivery of high-stakes enterprise AI engagements focused on Agentic AI and Generative AI solutions, managing scope, timeline, budget, and execution from initiation to successful deployment.
- • Serve as the primary technical and strategic liaison between enterprise client stakeholders (including C-suite) and DataRobot’s engineering teams, translating business objectives into precise technical requirements and vice versa.
- • Identify and mitigate technical risks early in AI project lifecycles, particularly around data infrastructure, API integrations, agent logic, latency trade-offs, and RAG architectures, ensuring alignment with critical project paths.
- • Drive adoption of autonomous AI workflows by guiding clients through operational changes required to integrate Agentic AI into daily business processes, ensuring sustainable use beyond initial delivery.
- • Manage agile delivery cycles including sprint planning, daily stand-ups, and sprint reviews, maintaining team velocity and clear directional focus across multidisciplinary AI delivery teams.
- • Cultivate trusted, long-term relationships with key client sponsors, proactively managing expectations, resolving escalations, and navigating complex organizational dynamics to ensure project success and client satisfaction.
- • Define and track measurable KPIs and ROI metrics to align AI deliverables with strategic business outcomes, ensuring each engagement delivers quantifiable business value.
- • Apply disciplined consulting practices in project governance, documentation, client communication, and change management to uphold high standards of professionalism and accountability.
- • Operate with a consulting DNA, drawing on experience in management or technology consulting environments to structure engagements, manage client deliverables, and ensure clarity across all stakeholder levels.
- • Lead cross-functional teams composed of AI Engineers, Data Scientists, and Solution Architects, coordinating efforts to deliver complex predictive and generative AI solutions at scale.
- • Maintain technical fluency in cloud infrastructure (AWS, Azure, GCP), system architectures, and the software development lifecycle (SDLC) to effectively collaborate with engineering teams on implementation challenges.
- • Stay current on advancements in GenAI and Agentic AI systems, including non-deterministic behavior, MCP servers, retrieval-augmented generation (RAG), and deployment patterns, to advise clients and teams accurately.
🎯 Requirements
- • 7+ years of professional experience delivering complex software or data products for enterprise clients
- • Hybrid background in technical roles (e.g., Software Engineer, Solution Architect) with progression into client-facing leadership roles (e.g., Engagement Manager, Technical Program Manager)
- • Experience managing data science or machine learning projects
- • Technical undergraduate degree in Computer Science, Engineering, or related field; MBA preferred
- • Experience working in a management consulting or technology consulting environment (Big 4 or boutique)
- • Familiarity with GenAI and Agentic AI systems (e.g., non-deterministic behavior, latency trade-offs, MCP servers, RAG architectures)
🏖️ Benefits
- • Medical, Dental & Vision Insurance
- • Flexible Time Off Program
- • Paid Holidays
- • Paid Parental Leave
- • Global Employee Assistance Program (EAP)
- • Competitive pay and benefits tailored to location and local legal requirements
Skills & Technologies
About DataRobot, Inc.
DataRobot provides an enterprise AI platform that automates the end-to-end process for building, deploying, and managing machine-learning models at scale. Founded in 2012, the company serves industries including finance, healthcare, retail, and manufacturing, enabling data scientists and business analysts to create predictive analytics without deep coding expertise. The platform integrates with existing data infrastructure, offers governance and monitoring tools, and supports on-premise, cloud, and hybrid deployments. DataRobot emphasizes responsible AI practices and model interpretability to help organizations operationalize artificial intelligence while maintaining compliance and transparency.
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