1 day ago

Forward Deployed AI Engineer (Senior/Principal Level)

✓ 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 design technical AI use cases and ship scalable full-stack AI/ML solutions on Cloudera. Partner from early prototype to production readiness, advise customer leaders on AI roadmaps and architectures, and codify winning solution patterns into reference architectures and playbooks. Drive AI capability by mentoring teams and feeding customer signals back to product to improve the AI platform.

Location: Ireland

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Build and prototype full-stack AI/ML applications on Cloudera to demonstrate how AI and agentic systems solve enterprise use cases.
•Work directly with customer teams to move AI and agentic use cases from early prototype to production readiness.
•Advise customer leaders on AI roadmaps, solution design, deployment, and AI use cases.
•Standardize successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams and channel customer and field signals back to Product teams to improve AI platforms and products.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone Reimbursement

Key Requirements

•7+ years building and deploying production-grade systems, including 2–4 years building ML systems or GenAI/agentic applications.
•Strong hands-on software, data engineering, and applied AI/ML skills to build full-stack ML 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.
•Ability to design scalable enterprise AI solution architectures aligned to security, governance, and compliance standards.

Experience:7+ years

Education:Bachelor's

Skills:MentorshipCollaborationHigh agencyThought leadershipCustomer engagement

Tech Stack:RAGLLMOpsMLOpsAWSAzureGCPSparkIcebergNiFiNVIDIA 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 (Senior/Principal Level)

✓ 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: Ireland

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Director level

Key Responsibilities

•Build and prototype full-stack AI/ML applications on Cloudera to demonstrate how AI and agentic systems solve enterprise use cases.
•Work directly with customer teams to move AI and agentic use cases from early prototype to production readiness.
•Advise customer leaders on AI roadmaps, solution design, deployment, and AI use cases.
•Standardize successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams and channel customer and field signals back to Product teams to improve AI platforms and products.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPhone Reimbursement

Key Requirements

•7+ years building and deploying production-grade systems, including 2–4 years building ML systems or GenAI/agentic applications.
•Strong hands-on software, data engineering, and applied AI/ML skills to build full-stack ML 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.
•Ability to design scalable enterprise AI solution architectures aligned to security, governance, and compliance standards.

Experience:7+ years

Education:Bachelor's

Skills:MentorshipCollaborationHigh agencyThought leadershipCustomer engagement

Tech Stack:RAGLLMOpsMLOpsAWSAzureGCPSparkIcebergNiFiNVIDIA 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