Engineering Vice President, AI Engineering - Professional Services California, US - Remote

Location: California

Job Description

Data Robot 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 aRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on Data Robot for AI that makes sense for their business — today and in the future. The VP AI Engineering plays a critical leadership role in shaping and executing our AI strategy. This leader will guide a global team of AI engineers and architects in designing, building, and deploying cutting-edge AI solutions—ranging from predictive models to advanced Generative AI systems and agentic architectures—that deliver measurable business value for our most strategic customers. As a trusted thought partner to senior executives, the VP will bridge business strategy and technical execution, ensuring that every AI initiative drives tangible outcomes. This role requires a visionary who thrives at the intersection of innovation, leadership, and customer impact—someone who can scale teams, accelerate delivery, and champion the responsible and strategic adoption of AI across the enterprise.

Key Responsibilities

• Define and execute the vision for AI engineering in alignment with organizational strategy and customer needs.
• Drive the roadmap for AI innovation—spanning predictive, generative, and agentic AI capabilities—to position the organization as a leader in applied AI.
• Partner cross-functionally with Product, Professional Services, and Go-to-Market leaders to translate AI potential into scalable, high-impact solutions.

Team & Capability Development

• Build, mentor, and scale a world‑class team of AI engineers and applied scientists, fostering a culture of innovation, accountability, and continuous learning.
• Establish standards and best practices for AI development, deployment, and operational excellence (MLOps, governance, and model lifecycle management).
• Ensure the team’s expertise spans modern AI stacks, including LLMs, RAG systems, vector databases, and agentic frameworks such as Lang Graph, CrewAI, and Llama Index.

Customer Impact & Delivery Excellence

• Partner with enterprise customers to identify high‑value use cases, define technical architectures, and ensure successful delivery of AI solutions that drive business outcomes.
• Oversee the design, development, and deployment of scalable AI systems leveraging the Data Robot platform and open‑source tools.
• Champion technical quality, security, and performance across all AI applications and integrations.

Innovation & Thought Leadership

• Serve as an executive‑level advisor on emerging AI trends, technologies, and ethical frameworks.
• Represent the organization in strategic customer engagements, industry forums, and executive briefings.
• Drive internal knowledge sharing, ensuring learnings and innovations are systematically captured and scaled across teams and regions.

Knowledge, Skills and Abilities AI & Machine Learning Expertise

• Deep technical understanding of applied AI—including Generative AI (LLMs, RAG), agentic AI, and predictive modeling.
• Strong programming proficiency in Python and related ML/AI libraries (pandas, Num Py, scikit‑learn, etc.).
• Expertise in AI solution design, architecture, and deployment on cloud platforms (AWS, Azure, GCP).

Engineering Leadership

• Proven experience leading distributed engineering or applied AI teams, balancing technical depth with people leadership.
• Demonstrated success building scalable AI solutions with secure, containerized infrastructure (Docker, Kubernetes).
• Strong command of software and systems design principles, API development, and MLOps lifecycle management.

Business Acumen & Communication

• Exceptional ability to connect technical execution with business value.
• Skilled communicator who can influence across technical and executive audiences.
• Experience engaging with customers, shaping strategy, and driving adoption of transformative technology.

Requisite Education and Experience /

Minimum Qualifications

• Experience:

10+ years of experience in AI, software engineering, or data science, including at… Apply tot his job Apply To this Job