Director, AI Platforms

Accountabilities:
The Director, AI Platforms will lead the development and evolution of enterprise AI platform capabilities, ensuring robust infrastructure, operational excellence, and alignment with business objectives. This role requires strong technical leadership, strategic thinking, and the ability to collaborate across multiple teams and stakeholders. Define and execute AI platform strategy, including architecture decisions and long-term technical direction for AI-first platforms. Build and maintain scalable, reliable, and observable AI infrastructure that supports production workloads and internal delivery teams. Establish platform standards, service expectations, and consumption models to enable efficient AI adoption across teams. Manage relationships with AI technology vendors, including contract discussions, performance monitoring, and issue escalation management. Lead incident management, troubleshooting, and continuous improvement initiatives for AI platform operations. Partner with engineering, quality, compliance, and infrastructure teams to ensure platforms meet technical, security, and regulatory requirements. Drive platform readiness for enterprise AI applications, including GenAI workloads, AI assistants, and advanced automation capabilities. Lead and mentor a high-performing platform engineering team, supporting talent development and fostering a collaborative engineering culture. Promote best practices in AI infrastructure, operational excellence, and scalable platform delivery. Requirements: The ideal candidate is an experienced technology leader with a strong background in platform engineering, AI infrastructure, and enterprise-scale technology delivery. They should combine deep technical expertise with strong communication and leadership skills. Bachelor’s degree in Computer Science, Engineering, or a related technical field. 10+ years of experience in platform engineering, data engineering, AI/ML infrastructure, or related technical roles. Proven experience operating AI platforms in production environments. Strong knowledge of AI infrastructure components, including GenAI runtimes, vector databases, agent orchestration, MLOps tooling, and evaluation frameworks. Hands-on experience with cloud platforms such as AWS or Azure. Deep understanding of cloud-based platform engineering principles and architectural trade-offs. Experience managing technology vendors, including contract negotiations, service performance, and commercial relationships. Strong written and verbal communication skills, with the ability to collaborate effectively with technical and business stakeholders. Experience working in regulated environments, with familiarity in compliance-driven industries preferred. Strong organizational, problem-solving, and strategic planning abilities. Ability to lead engineering teams, develop talent, and operate effectively in a fast-moving environment. Preferred qualifications: Master’s degree in a technical discipline. Experience with enterprise AI platforms, custom AI assistants, or advanced GenAI solutions. Familiarity with platforms such as Palantir Foundry, Copilot Studio, Anthropic-based solutions, or similar AI ecosystems. Experience working within shared infrastructure or enterprise platform organizations. Benefits: Opportunity to lead enterprise-scale AI platform initiatives with significant business impact. Flexible remote working environment. Opportunity to collaborate with global teams across engineering, AI, infrastructure, and business functions. Continuous learning and professional development opportunities. Ability to influence AI strategy and innovation within a growing technology environment. Supportive culture focused on flexibility, collaboration, and meaningful contributions. Opportunity to build and mentor high-performing technical teams.

How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
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