Lead AI Engineer

Lead AI Engineer - Professional Services

As the lead AI engineer within our professional services team, you will be a strategic leader and executive advisor, responsible for driving the technical vision and successful delivery of our most complex and strategic AI programs with our top-tier customers.
You will be part of a high-performing team of AI engineers, establish architectural best practices for agentic AI deployments, and ensure that all solutions translate into exceptional, measurable business value. This role requires a balance of deep technical expertise, a proven background in software engineering practices and architectures with executive-level communication and P&L accountability for large professional service engagements.

Key Responsibilities:

• Executive & strategic engagement: Serve as the most senior technical leader on major engagements, advising C-level executives and key stakeholders on their AI strategy, architectural roadmap, and governance model.
• Program ownership & governance: Own the technical success of the professional services portfolio, setting the technical standards, ensuring solution quality, and overseeing the deployment of advanced AI applications, including agentic AI and complex GenAI/RAG systems.
• Technical architecture & standards: Define the architectural blueprint and MLOps best practices for building robust, scalable, and secure AI solutions that leverage the DataRobot platform and cutting-edge open-source tools.
• Thought leadership: Act as a recognized subject matter expert in the AI/ML community, representing DataRobot at industry conferences, publishing technical content, and driving internal innovation.
• Revenue and utilization management: Drive successful program execution, managing technical risk and ensuring high customer satisfaction, which directly contributes to achieving regional revenue targets.
• Travel: Ability to travel up to 50% across the region to support customers across GCC.
• Language: Proficient in Arabic is preferred but not critical.

Knowledge, Skills and Abilities:

• Strategic AI & architectural expertise:
  Expertise in full-stack development, enterprise software architecture, and the implementation of modern agentic AI frameworks.
  Deep, proven expertise in defining and implementing end-to-end AI/ML and generative AI application architectures, including agentic AI frameworks (LangGraph, CrewAI, Llama Index), RAG, and large-scale predictive modeling systems.
  Expertise in setting MLOps strategy for model CI/CD, governance, and enterprise-level scaling.
  Deep proficiency in containerization (Docker/Kubernetes), and building secure, production-grade REST APIs.
• Leadership & consulting:
  Exceptional executive-level verbal and written communication skills, with the ability to lead discussions, present complex technical roadmaps, and influence decision-makers across business and technology domains.
  Demonstrable track record in a highly visible client-facing or consulting leadership role.

Requisite Education and Experience / Minimum Qualifications:

• Experience: Approximately 8-10 years of progressive hands-on experience in software development, agentic AI frameworks, or a similar technical role.
• Education: A CS degree, MS or Ph.D. preferred in computer science, artificial intelligence, engineering, or a related quantitative field.
• Cloud experience: Expert-level, hands-on experience with at least one major cloud platform (AWS, Azure, or GCP) and on-premise deployment experience, with a focus on enterprise architecture and security.
• DataRobot experience: Expert familiarity with the DataRobot AI platform is a strong plus.