Applied AI Specialist (AI)

Location: Hybrid; South Korea-Seoul, Korea, Republic of, with other locations in Japan>Tokyo

Company

hirify.global provides enterprise data platforms that help organizations transform complex data into actionable insights and operationalize AI securely at scale.

What you will do

• Lead technical, hands-on AI discovery workshops with enterprise customers and strategic ecosystem partners including NVIDIA.
• Discover, scope, validate, and prioritize private AI use cases with measurable business outcomes.
• Assess data architecture, governance, security, infrastructure constraints, and data gravity challenges affecting AI deployment feasibility.
• Build lightweight proofs of concept, reference architectures, technical demonstrations, and solution frameworks.
• Define technical requirements, data specifications, success criteria, architectural recommendations, and scoped outcomes for handoff to Forward Deployed Engineering teams.
• Develop regional domain expertise and document reusable AI use cases, architectural patterns, and implementation frameworks.

Requirements

• Strong technical foundation in data science, with hands-on comfort using code, APIs, notebooks, development frameworks, and enterprise architectures.
• Practical experience building or supporting AI applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
• Ability to discuss model architectures, training and evaluation methods, inference patterns, and production deployment considerations across enterprise AI workloads.
• Proven experience in technical pre-sales, solution architecture, consulting, customer engineering, or a similar role involving discovery, qualification, and design of complex enterprise technology initiatives.
• Ability to evaluate data quality, governance, security, compliance, operational readiness, and infrastructure constraints for private AI deployments.
• Exceptional communication skills for engaging technical and executive audiences and connecting business outcomes with practical implementation strategies.
• Experience with Python, APIs, cloud-native architectures, data pipelines, MLOps, and modern AI development ecosystems.

Nice to have

• Experience with NVIDIA AI Enterprise, NIMs, NeMo, RAPIDS, or accelerated computing platforms.
• Experience delivering customer-facing workshops, design sessions, or architecture engagements.
• Experience moving AI projects from proof of concept into production environments.
• Familiarity with enterprise data platforms, governance frameworks, and hybrid cloud architectures.

Culture & Benefits

• Centralized platform support for cloud credentials, environment setup, and workshop preparation.
• Clear operational boundaries between discovery and validation work and production implementation by Forward Deployed Engineering teams.
• Direct collaboration with AI practitioners, strategic ecosystem partners, and enterprise innovators.
• Flexible work-from-home policy, generous paid time off, unplugged days, and work-life balance support.
• Mental and physical wellness programs, phone and internet reimbursement, continued career development, comprehensive benefits, paid volunteer time, and employee resource groups.