| Job Description: |
Lead the AI engineering and delivery function and own the end-to-end AI delivery lifecycle, including development, DevOps, AI Ops, and LLM Ops for industrial-scale AI solutions.
Key responsibilities
• Define and operationalize the AI engineering and delivery process flow, including tools, standards, release practices, and lifecycle controls.
• Build and lead the delivery side of the organization, covering development and operations as two core pillars.
• Establish baseline KPIs for Engineering and DevSecOps functions.
• Evaluate and bring in ADLC and AI in SDLC practices with partners and select suitable vendor and opensource products to build the future stack that will drive KPI improvements
• Partner closely with enterprise architecture leadership to align engineering tooling and implementation choices with enterprise standards.
• Collaborate with CIO, CISO, CFO, risk, and legal stakeholders to ensure delivery practices align with enterprise-wide AI governance expectations.
• Stand up pod-based or scrum-team-based operating structures to deliver priority AI use cases while refining the broader framework.
• Drive fast execution, iterative learning, and measurable outcomes instead of long planning cycles without delivery.
Role requirements
• Demonstrated experience building greenfield AI ecosystems, not only isolated agents or point AI use cases.
• Experience with creating internal developer platforms and drive adoption of it,
• Strong hands-on leadership style, with willingness to work on-site and operate at a fast pace in close partnership with internal leadership.
• Deep familiarity with DevOps, AI Ops, LLM Ops, and industrialized AI delivery methods.
• Ability to define process, select tools, coach teams, and adjust rapidly based on observed bottlenecks.
• Strong communication skills with the ability to operate at both executive and engineering depth.
Role Descriptions: AI-led DevSecOps Leader
Skills: Digital : Cloud DevOps~AI for Leadership
Experience Required: 10 & Above
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