Applied AI Specialist

Cloudera
Prague
Workplace: RemoteFull timeFunction: Data Science & Machine LearningSkills: ["Technical communication","Workshops facilitation","Customer discovery","Data readiness assessment","Solutioning"]

Identify, validate, and establish technical conviction for high-impact private AI use cases for enterprise customers. Lead technical discovery workshops (including hands-on sessions with partners such as NVIDIA), scope AI opportunities, and assess feasibility across data readiness, governance, security, and infrastructure constraints. Translate qualified opportunities into engineering blueprints and reusable technical assets, then hand off scoped outcomes to Forward Deployed Engineers for production delivery.

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FursaFursa
Cloudera
Cloudera
1 month ago

Applied AI Specialist

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 27 days agoStatus: Live

Job Summary

Identify, validate, and establish technical conviction for high-impact private AI use cases for enterprise customers. Lead technical discovery workshops (including hands-on sessions with partners such as NVIDIA), scope AI opportunities, and assess feasibility across data readiness, governance, security, and infrastructure constraints. Translate qualified opportunities into engineering blueprints and reusable technical assets, then hand off scoped outcomes to Forward Deployed Engineers for production delivery.
Location: Prague
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Lead AI discovery workshops by partnering with ecosystem providers (including NVIDIA) to design and facilitate hands-on sessions that identify and prioritize private AI opportunities.
  • •Discover and scope high-value AI use cases with enterprise customers to target measurable business outcomes and production suitability.
  • •Evaluate enterprise AI readiness by assessing data architecture, governance, infrastructure constraints, security considerations, and data gravity challenges.
  • •Develop regional domain leadership as a subject matter expert within a regional pod, transferring successful AI patterns across customer segments.
  • •Build and package technical assets (proofs of concept, reference architectures, demos, and solution frameworks) and define engineering blueprints for handoff to FDE teams.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone ReimbursementVolunteer Time

Key Requirements

  • •Strong technical foundation in data science, with comfort working directly with code, APIs, notebooks, development frameworks, and enterprise architectures.
  • •Hands-on experience building or supporting AI applications across areas such as machine learning, deep learning, computer vision, time-series analytics, predictive modeling, anomaly detection, and generative AI.
  • •Proven success in enterprise discovery and solutioning (e.g., technical pre-sales, solution architecture, consulting, or customer engineering) for complex enterprise initiatives.
  • •Ability to assess data readiness, including data quality, governance, security, compliance, operational readiness, and infrastructure constraints for private AI deployments.
  • •Experience communicating effectively with both technical and executive audiences to connect business outcomes with implementation strategies.
Experience:EnterpriseAIMachine learning
Skills:Technical communicationWorkshops facilitationCustomer discoveryData readiness assessmentSolutioning
Tech Stack:PythonAPIsNotebooksMachine learningDeep learningComputer visionPredictive analyticsGenerative AIAgentic systemsTime-series analyticsPredictive modelingAnomaly detectionMLOpsCloud-native architecturesData pipelinesEnterprise data platformsNVIDIA AI EnterpriseNIMsNeMoRAPIDs

Company Brief

Cloudera
Provides a hybrid data platform for managing, analyzing, and securing enterprise data across cloud and on-premises environments, enabling machine learning, analytics, and data engineering at scale.
Industry: Data Infrastructure
Company Size: Enterprise (1,001+ employees)
Revenue: USD 500M to 1B
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 2008
Glassdoor
Glassdoor: 3.8
WebsiteLinkedIn