1 day ago

Forward Deployed AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Embed with strategic enterprise customers to prototype and productionize full-stack AI and agentic applications on Cloudera. You’ll partner with customer teams to move use cases from early pilots to readiness, advise leaders on AI roadmaps, and codify repeatable solution patterns into reference architectures and internal playbooks. You’ll also mentor teams and feed customer signals back into Cloudera’s AI platform and products, grounded in strong LLMOps/MLOps practices.

Location: Prague

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and prototype full-stack AI applications on Cloudera to solve enterprise use cases using AI and agentic systems.
•Work directly with strategic customers to take AI/agentic use cases from early prototype toward production readiness.
•Advise customer leaders on AI roadmaps, use case prioritization, deployment considerations, and alignment with business goals.
•Codify successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, contribute to growing AI capability, and channel customer signals back to product teams to improve the AI platform and products.

Pay and Benefits

Perks:Paid LeavePhone ReimbursementWellness StipendVolunteer Time

Key Requirements

•7+ years building and deploying production-grade systems, including 2-3 years building generative AI or agentic applications.
•Strong hands-on software engineering, data engineering, and applied AI/ML experience building full-stack AI or agentic systems with modern AI frameworks and tooling.
•Experience with foundation models, context engineering, fine-tuning, semantic search, Retrieval-Augmented Generation (RAG), and agentic workflows.
•Deep understanding of LLMOps/MLOps practices including evaluation, observability, serving, monitoring, and lifecycle management.
•Experience designing and implementing scalable enterprise AI solution architectures aligned to security, governance, and compliance standards.

Experience:7+ yearsEnterprise softwareArtificial intelligenceMachine learningLLMOpsMLOpsGenerative AIAgentic AI

Skills:Hands-on engineeringMentorshipCollaborationCustomer engagementAutonomy

Tech Stack:Generative AIAgentic systemsFoundation modelsContext engineeringFine-tuningSemantic searchRetrieval-Augmented Generation (RAG)LLMOpsMLOpsEvaluationObservabilityModel servingMonitoringAWSAzureGCPSparkIcebergNiFiNVIDIA GPUs

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: 3.8

Website LinkedIn

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Cloudera

1 day ago

Forward Deployed AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 10 hours agoStatus: Live

Job Summary

Location: Prague

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Mid level

Key Responsibilities

•Build and prototype full-stack AI applications on Cloudera to solve enterprise use cases using AI and agentic systems.
•Work directly with strategic customers to take AI/agentic use cases from early prototype toward production readiness.
•Advise customer leaders on AI roadmaps, use case prioritization, deployment considerations, and alignment with business goals.
•Codify successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, contribute to growing AI capability, and channel customer signals back to product teams to improve the AI platform and products.

Pay and Benefits

Perks:Paid LeavePhone ReimbursementWellness StipendVolunteer Time

Key Requirements

•7+ years building and deploying production-grade systems, including 2-3 years building generative AI or agentic applications.
•Strong hands-on software engineering, data engineering, and applied AI/ML experience building full-stack AI or agentic systems with modern AI frameworks and tooling.
•Experience with foundation models, context engineering, fine-tuning, semantic search, Retrieval-Augmented Generation (RAG), and agentic workflows.
•Deep understanding of LLMOps/MLOps practices including evaluation, observability, serving, monitoring, and lifecycle management.
•Experience designing and implementing scalable enterprise AI solution architectures aligned to security, governance, and compliance standards.

Experience:7+ yearsEnterprise softwareArtificial intelligenceMachine learningLLMOpsMLOpsGenerative AIAgentic AI

Skills:Hands-on engineeringMentorshipCollaborationCustomer engagementAutonomy

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: 3.8

Website LinkedIn