Job description for AI Solutions & Platform Lead at PT Eka Nusantara Gemilang
AI Solutions & Platform Lead
Role Purpose
Build and lead AI solutions and platform capability, including the transition, operation, and continuous enhancement of AI platforms and production use cases, while establishing scalable and governed AI delivery practices.
Key Responsibilities
- AI Solutions: Lead the assessment, design, development, productionization, and continuous improvement of AI and GenAI solutions based on business needs.
- AI Platform & Orchestration: Establish and operate scalable AI platform capabilities covering model lifecycle, orchestration, APIs, deployment, monitoring, and integration.
- AI Solutions & Platform Transition: Establish operational readiness, platform reliability, and continuous improvement practices for AI solutions and production workloads.
- AI Architecture & Standards: Define AI architecture principles, technical standards, reusable components, and integration patterns in coordination with Technology Strategy & Governance.
- AI Operations & Performance: Establish monitoring, reliability, cost, performance, and lifecycle practices for production AI workloads and platforms.
- AI Governance & Risk: Ensure AI solutions follow applicable security, privacy, governance, and risk requirements in coordination with GRC and relevant technology functions.
- People & Capability Development: Build and develop the AI team, establish engineering practices, and reduce dependency on individual specialists through documentation and knowledge sharing.
Minimum Qualification
- Minimum Work Experience: Minimum 10 years of experience in AI, machine learning, data, software engineering, or technology platforms, including at least 5 years in a managerial or technical leadership role with responsibility for production AI solutions or platforms.
- Industry: Technology, System Integrator, Digital, AI, Software Development, Cloud, or related industries.
- Education Level: Bachelor's degree in Computer Science, Artificial Intelligence, Information Technology, Data Science, Engineering, or a related field.
Skill
- AI/ML solution architecture, GenAI/LLM, machine learning lifecycle, and production AI implementation
- AI platform, MLOps, model lifecycle, orchestration, APIs, data pipelines, and deployment
- Cloud and/or hybrid AI infrastructure, including GPU compute and scalable platform environments
- AI solution engineering, use-case assessment, prototyping, productionization, and optimization
- AI governance, security, responsible AI, model risk, data privacy, and technology standards
- Integration of AI capabilities with enterprise applications, digital platforms, and business processes
- Technology roadmap, vendor evaluation, platform selection, and solution cost/performance management
- Team leadership, capability development, stakeholder management, and cross-functional collaboration
