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Cloudera

Hybrid data platform for analytics

Applied AI Specialist

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedHybrid

About the Job

Requirements

  • Strong technical foundation in data science, including comfort working with code, application programming interfaces, notebooks, development frameworks, and enterprise architectures.
  • Practical experience building or supporting artificial intelligence applications across machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative artificial intelligence; ability to discuss model architectures, training and evaluation methodologies, inference patterns, and production deployment considerations across enterprise artificial intelligence workloads.
  • Proven success in technical pre-sales, solution architecture, consulting, customer engineering, or similar roles involving discovery, qualification, and design of complex enterprise technology initiatives.
  • Ability to evaluate data quality, governance, security, compliance, operational readiness, and infrastructure constraints affecting private artificial intelligence deployments.
  • Ability to engage technical and executive audiences and facilitate conversations connecting business outcomes with practical implementation strategies.
  • Experience with Python, application programming interfaces, cloud-native architectures, data pipelines, machine learning operations, and modern artificial intelligence development ecosystems.

Responsibilities

  • Partner with strategic ecosystem providers, including NVIDIA, to design and facilitate hands-on technical workshops that identify, validate, and prioritize private artificial intelligence opportunities.
  • Conduct technical and business discovery with enterprise customers to identify artificial intelligence workloads that can deliver measurable business outcomes and are suitable for production deployment.
  • Assess data architecture, governance requirements, infrastructure constraints, security considerations, and data gravity challenges to determine the feasibility of private artificial intelligence deployments.
  • Serve as a subject matter expert within the regional pod, build expertise in one or more strategic industries, and help transfer successful artificial intelligence patterns across customer segments.
  • Develop lightweight proofs of concept, reference architectures, technical demonstrations, and solution frameworks to help customers validate feasibility before full-scale implementation.
  • Translate qualified opportunities into technical requirements, data specifications, success criteria, architectural recommendations, and scoped outcomes for handoff to Forward Deployed Engineer teams.
  • Document successful use cases, architectural patterns, and implementation frameworks for reuse across customers, industries, and regions.

Desired Qualifications

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

About the Company

Cloudera

Hybrid data platform for analytics

Cloudera provides a data management and analytics platform for large organizations. Its core product, the Cloudera Data Platform (CDP), is a hybrid data platform that lets companies store, manage, and analyze data across on‑premises, cloud, and edge environments. Users subscribe to software and also access professional services and support to implement and optimize their data solutions. The platform processes big data to deliver insights, enabling digital transformation and competitive differentiation for industries like finance, healthcare, telecommunications, and retail. Cloudera differentiates itself with a unified, multi-environment data platform designed for large enterprises, combined with services to help customers deploy, optimize, and scale their data workloads. The company’s goal is to turn vast data into actionable insights that inform business decisions and drive innovation.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
2008

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