Enterprise AI Deployment Lead
Enterprise AI / Delivery · 1–5 years · Full-time · Korea · Open
About EBIT
EBIT started as an AI data company specializing in building, validating, and operating the high-quality training data that AI model development requires, and is now an AI solutions company expanding into Enterprise AI, Global GTM, and Physical AI.
EBIT provides an integrated data build service covering the entire process from data design to collection, processing, and quality control, along with custom data solutions optimized to each client's requirements. Since 2024 we have worked with big tech companies in Korea and abroad on high-complexity domain data projects across language, coding, STEM, and finance, establishing ourselves as an APAC partner. We are now growing fast, expanding into Enterprise AI solutions for corporate clients, Global GTM, and Physical AI areas such as robotics and autonomous driving.
About the Role
The Enterprise AI Deployment Lead turns enterprise clients' business problems into executable AI initiatives and owns everything from enterprise AI solution strategy and architecture design to production deployment, leading projects while communicating with executive-level stakeholders on the client side.
Responsibilities
Own enterprise AI transformation and deployment strategy
Assess the client's business goals and AI maturity, derive the key AI initiatives and their priorities, build the AI transformation roadmap and phased adoption strategy, and align direction and decisions with client executives.
Design enterprise AI solutions and architecture
Design the overall solution structure so that AI Agents, LLMs, RAG, and other AI technology integrate with the client's existing business systems and data platforms. Define the technical and data requirements for the build and own the AI system design direction for the client's environment.
Lead the full project lifecycle from PoC/Pilot to production deployment
Set scope, goals, KPIs, and phased schedules; plan the build and the transition to operations so that solutions validated in PoC/Pilot are applied in the real work environment; and keep reviewing adoption and business results after go-live.
Own communication across enterprise AI projects and executive stakeholders
Oversee multiple concurrent enterprise AI projects and coordinate collaboration between client executives, business and IT teams, and EBIT's engineering, data, and operations teams. Manage schedule, quality, key deliverables, and risks so projects run reliably.
Build the AI deployment methodology and operating model
Standardize what is learned across enterprise AI projects into EBIT's methodology and standard operating model, usable consistently from opportunity discovery through PoC/Pilot, build, and transition to operations.
Requirements
- Education: Bachelor's degree or higher (business, economics, industrial engineering, computer science, statistics, or information systems preferred)
- Experience: 5+ years as a project or program lead in enterprise AI/IT consulting, AI transformation, solution delivery, or digital transformation
- (Required) Project and communication skills: English proficiency sufficient to independently run meetings, workshops, presentations, and communication with US enterprise clients
- Experience structuring complex enterprise business problems and turning them into AI or technology-driven initiatives
- Strong understanding of AI/ML, LLMs, generative AI, RAG, AI Agents, and enterprise data/IT architecture
- Experience leading large technology projects end to end, from PoC/Pilot to build and operations
Preferred
- Project experience with global enterprise clients and overseas cross-functional teams
- Experience designing enterprise architecture on AWS, Azure, or GCP, or operating MLOps/LLMOps
- Enterprise AI project experience at a strategy/IT consulting firm, AI-native company, or cloud/SaaS company
- Experience building and deploying LLM/RAG/AI Agent-based enterprise solutions to production
- Experience integrating AI solutions with enterprise systems such as ERP, CRM, and data platforms
