DevOps Engineer

• Cloud infrastructure 및 hybrid infrastructure 환경에서 확장 가능하고 안정적인 DevOps 운영 기반을 설계, 구축, 운영합니다.
• CI/CD 도구를 안정적으로 운영하고, 성능, 가용성, 확장성, 운영 효율 측면에서 지속적으로 개선합니다.
• 패키지 및 아티팩트 관리 도구를 운영하며, 저장, 배포, 권한 관리, 보존 정책 등 운영 체계를 수립합니다.
• 빌드 및 검증 환경을 컨테이너 기반으로 표준화하고, 재현 가능하고 일관된 실행 환경을 구축합니다.
• 컨테이너 관리 도구 및 플랫폼을 운영하여 빌드/테스트 워크로드가 안정적으로 실행될 수 있는 환경을 제공합니다.
• CI/CD 시스템과 관련 플랫폼이 안정적으로 동작할 수 있도록 compute, storage, network, identity, access control 체계를 관리합니다.
• Infrastructure as Code 기반으로 DevOps 플랫폼과 인프라 구성을 표준화하고 자동화합니다.
• 서비스 가용성, 성능, 용량, 장애 복구, 백업, 모니터링 체계를 구축하고 운영합니다.
• 로그, 메트릭, 알림, 대시보드 등 observability 체계를 정비하여 운영 효율성과 문제 대응 속도를 높입니다.
• 보안 정책에 따라 credential 관리, 접근 제어, 감사 로그, 취약점 대응, 패치 관리 등 플랫폼 보안 운영을 수행합니다.

DevOps Platform – Cloud Infra Engineer

• Define and evolve reliability goals for production systems through SLIs, SLOs, error budgets, and meaningful operational metrics.
• Design and build observability foundations that make system behavior, user impact, performance bottlenecks, and failure modes measurable and actionable.
• Analyze production systems end-to-end, identify reliability risks across software, infrastructure, and networking boundaries, and drive architectural improvements.
• Improve change safety and failure recovery through better rollout strategies, capacity planning, load validation, graceful degradation, and incident learning loops.
• Reduce operational toil by building automation, internal tooling, and self-service workflows that make production systems easier to operate and harder to misuse.

Software Engineer, Site Reliability Engineer

• Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams.
• Influence joint account strategy and technical direction for high-priority opportunities.
• Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices.
• Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem.
• Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements.
• Guide AWS and partner teams through customer opportunities from early ideation to architecture design, prototyping, and production deployment.
• Act as a technical decision-maker and escalation point, de-risking complex implementations.
• Apply strong judgment to prioritize opportunities and allocate limited technical resources for maximum impact.
• Design and communicate end-to-end AI architectures leveraging OpenAI and AWS services.
• Build and guide development of prototypes, POCs, and reference implementations to accelerate adoption.
• Establish best practices for scalable, secure, and production-ready GenAI systems.
• Ensure solutions are designed for repeatability, extensibility, and partner-led delivery.
• Enable AWS and partners through scalable technical motions (workshops, playbooks, reference architectures, demos).
• Develop reusable solution patterns and assets that can be deployed independently by AWS teams and SIs.
• Mentor and uplift partner technical teams, accelerating their path to self-sufficiency.
• Scale impact by working through GSIs, RSIs, and ISVs, rather than relying solely on direct engagement.
• Partner closely with Alliances, Product, Engineering, GTM, and Enablement to align on strategy and execution.
• Act as a bridge between field and product, delivering high-signal insights to inform roadmap and prioritization.
• Contribute to internal knowledge systems and help define standards, patterns, and playbooks for the ADE function.

Partner AI Deployment Engineer – AWS

• Own the strategy and operating model of the AI Deployment Engineering team in Korea, ensuring alignment with company objectives and the evolving needs of our customers.
• Lead, build, and mentor a team of high-performing AI Deployment Engineers to deliver exceptional customer outcomes, as demonstrated by production customer applications and increased API adoption.
• Serve as the technical advocate for our customers, synthesizing their needs to develop the Research and Applied Product/Engineering roadmaps.
• Act as the primary technical escalation point during development, fostering trust and maintaining direct communication with executive-level stakeholders.
• Serve as an industry thought leader, championing the safe and innovative application of our technology across various sectors.

Manager, AI Deployment Engineering – Korea

• Lead the Facilitation of Failure Mode and Effects Analysis (FMEA) sessions
• Evaluate equipment design & layouts during the design phase
• Provide technical guidance to project teams
• Complete critical spare needs evaluations
• Develop initial inspection, testing and maintenance plans
• Investigate and analyze plant equipment failures
• Develop approaches for projecting asset lifecycle costs
• Provide guidance to junior engineers and maintenance technicians
• Support Plant Operations & Maintenance functions
• Provide remote support to all ALAM projects globally

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