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: 13 hours agoStatus: Live

Job Summary

Embed with strategic enterprise customers to rapidly pilot and deploy generative AI and agentic use cases. Build and prototype full-stack AI applications on Cloudera, partner through production readiness, and advise on AI roadmaps and deployment considerations. Standardize successful solutions into repeatable reference architectures and playbooks, while applying strong LLMOps/MLOps practices for evaluation, observability, serving, and monitoring. Mentor teams and channel customer learnings back to product.

Location: Austria

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Build and prototype full-stack AI applications on Cloudera to demonstrate AI and agentic systems for real enterprise use cases
•Work directly with customer teams to take AI and agentic use cases from early prototypes to production readiness
•Advise customer leaders on AI roadmaps, use case prioritization, and deployment considerations aligned to business goals
•Codify solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks
•Mentor Cloudera teams and feed field/customer signals back to product teams to improve the AI platform and products

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone ReimbursementPaid VolunteerEmployee Resource

Key Requirements

•5+ 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 skills to build full-stack AI applications or agentic systems
•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 AI solution architectures aligned to enterprise standards (security, governance, compliance)

Experience:5+ yearsEnterpriseGenerative AI

Skills:Hands-on engineeringMentorshipCustomer engagementCollaborationHigh agency

Tech Stack:ClouderaGenerative AIAgentic systemsFoundation modelsContext engineeringFine-tuningSemantic searchRetrieval-Augmented Generation (RAG)LLMOpsMLOpsAWSAzureGCPSparkIcebergNiFiNVIDIA GPUsInference optimizationModel servingDistributed AI workloads

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: 13 hours agoStatus: Live

Job Summary

Location: Austria

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Build and prototype full-stack AI applications on Cloudera to demonstrate AI and agentic systems for real enterprise use cases
•Work directly with customer teams to take AI and agentic use cases from early prototypes to production readiness
•Advise customer leaders on AI roadmaps, use case prioritization, and deployment considerations aligned to business goals
•Codify solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks
•Mentor Cloudera teams and feed field/customer signals back to product teams to improve the AI platform and products

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone ReimbursementPaid VolunteerEmployee Resource

Key Requirements

•5+ 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 skills to build full-stack AI applications or agentic systems
•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 AI solution architectures aligned to enterprise standards (security, governance, compliance)

Experience:5+ yearsEnterpriseGenerative AI

Skills:Hands-on engineeringMentorshipCustomer engagementCollaborationHigh agency

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