AI Engineer 경력 구성원 영입

[SK바이오팜] AI Engineer 경력 구성원 영입

[Role Description]

- The AI Engineer will join the AI Transformation (AX) team, driving enterprise-wide AI initiatives in direct partnership with business functions—including Supply Chain Management and Commercial.

- The team also partners with Staff and corporate functions, converting manual, step-driven workflows into intelligent, automated services.

- This is a hands-on individual contributor role, working with the team lead and business stakeholders to identify practical opportunities across the AX project portfolio.

- The engineer will define an appropriate technical approach, and build, deploy, and operate production-ready AI services.

- Within this portfolio, the engineer will productionize AI models and prototypes from AI scientists into robust, scalable applications.

- The engineer will also build AI-native services such as agentic AI systems, multi-agent workflows, LLM-based applications, and RAG pipelines.

- The role carries a high degree of freedom in technology choices, and calls for openness to a wide range of stacks and frameworks, selecting and adapting them to fit the available infrastructure.

- Building visibility and observability into pipelines from the outset, and using that instrumentation to monitor, diagnose, and continuously improve the system architecture, is a core part of the work.

- Because AX projects span multiple functions and move at different speeds, this role rewards broad, cross-functional experience over deep specialization in a single domain.

- Success depends as much on communicating well with non-technical stakeholders and learning unfamiliar technologies by doing as it does on engineering depth.

- Staying current with emerging AI and engineering trends is essential, and contributions to shared best practices and reusable templates that accelerate project delivery are encouraged and valued.

[Education]

- Bachelor's degree or higher.

[Major]

- Computer Science, Engineering, or a related field.

[Experience]

- 5 to 15 years of professional experience, including building and deploying machine learning or AI systems in production.

- An awarded Ph.D. in a relevant field counts as 5 years toward this requirement (other degrees do not count toward the years requirement).