Forward Deployed AI Engineer

Cloudera
Austria
Workplace: RemoteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Hands-on engineering","Mentorship","Customer engagement","Collaboration","High agency"]

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.

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FursaFursa
Cloudera
Cloudera
1 month 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: 24 days 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
Glassdoor: 3.8
WebsiteLinkedIn