1 day ago
Tokyo, Japan or Seoul, Korea, SouthStaff+
Responsibilities
- Lead technical, hands-on AI discovery workshops with enterprise customers and strategic ecosystem partners, including NVIDIA.
- Discover, scope, validate, and prioritize high-value private AI use cases suitable for production deployment.
- Assess enterprise data readiness, governance, security, compliance, infrastructure constraints, and data-gravity considerations.
- Serve as a regional AI subject matter expert and develop expertise in strategic industries.
- Build lightweight proofs of concept, reference architectures, technical demonstrations, and solution frameworks.
- Translate qualified opportunities into technical requirements, data specifications, success criteria, architectural recommendations, and scoped outcomes for Forward Deployed Engineering teams.
- Document reusable AI use cases, architectural patterns, and implementation frameworks.
- Engage technical and executive audiences to connect business outcomes with practical implementation strategies.
Requirements
- Strong technical foundation in data science and comfort working with code, APIs, notebooks, development frameworks, and enterprise architectures.
- Practical experience building or supporting AI applications involving machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
- Ability to discuss model architectures, training and evaluation methodologies, inference patterns, and production deployment considerations.
- Proven experience in technical pre-sales, solution architecture, consulting, customer engineering, or comparable enterprise technology discovery and solutioning roles.
- Ability to evaluate data quality, governance, security, compliance, operational readiness, and infrastructure constraints.
- Exceptional communication skills with technical and executive stakeholders.
- Experience with Python, APIs, cloud-native architectures, data pipelines, MLOps, and modern AI development ecosystems.
- Experience with NVIDIA AI Enterprise, NIMs, NeMo, RAPIDS, or accelerated computing platforms is advantageous.
- Customer-facing workshop, design-session, or architecture-engagement experience is advantageous.
- Experience moving AI projects from proof of concept into production and familiarity with enterprise data platforms, governance frameworks, and hybrid cloud architectures are advantageous.
Benefits
- Generous paid time off and Unplugged Days supporting work-life balance.
- Flexible work-from-home policy.
- Mental and physical wellness programs.
- Phone and internet reimbursement program.
- Continued career development opportunities.
- Comprehensive benefits and competitive packages.
- Paid volunteer time and employee resource groups.
- Dedicated centralized workshop-platform support for environment setup, credentials, and workshop preparation.
- Opportunities to work with leading AI practitioners, ecosystem partners, and enterprise innovators, while developing regional industry expertise and influencing go-to-market strategy.
Tech Stack
NimPython
Categories
Solutions Engineering
About Cloudera
Cloudera builds the Cloudera Data Platform, an enterprise data stack for hybrid cloud and on‑premises environments that unifies data engineering, warehousing, streaming, and machine learning with governance. It sells subscriptions and managed services to large enterprises across regulated, data‑intensive industries. Founded in 2008 and headquartered in Santa Clara, the company was taken private in 2021 in a transaction led by Clayton, Dubilier & Rice (CD&R).