Cloudera

13 hours 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 prototype, build, and deploy full-stack generative AI and agentic applications using Cloudera. Partner with customer teams to move use cases from early pilots to production readiness, while advising on AI roadmaps and deployment considerations. Codify repeatable solution patterns into reference architectures and starter kits, mentor internal teams, and feed field learnings back to product to improve the AI platform.

Location: Singapore

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 demonstrate how AI and agentic systems solve enterprise use cases.
•Partner with strategic customers to drive AI and agentic use cases from early prototypes toward production readiness.
•Advise customer leaders on AI roadmaps, use case prioritization, and deployment considerations aligned to business goals.
•Codify successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, grow AI capability resources, and relay field and customer signals back to product teams to improve the AI platform and products.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPaid Volunteer

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 and applied AI/ML skills, building full-stack AI applications 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.
•Ability to engage with customer technical and executive audiences to translate needs into actionable technical strategy.

Experience:5+ years

Skills:MentorshipCollaborationProblem-solvingAutonomyCustomer-facing communication

Tech Stack:Generative AIAgentic systemsRetrieval-Augmented Generation (RAG)LLMOpsMLOpsFine-tuningSemantic searchAWSAzureGCPSparkIcebergNiFiNVIDIA 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

13 hours 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: Singapore

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 demonstrate how AI and agentic systems solve enterprise use cases.
•Partner with strategic customers to drive AI and agentic use cases from early prototypes toward production readiness.
•Advise customer leaders on AI roadmaps, use case prioritization, and deployment considerations aligned to business goals.
•Codify successful solution patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, grow AI capability resources, and relay field and customer signals back to product teams to improve the AI platform and products.

Pay and Benefits

Perks:Paid LeaveRemote WorkWellness StipendPaid Volunteer

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 and applied AI/ML skills, building full-stack AI applications 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.
•Ability to engage with customer technical and executive audiences to translate needs into actionable technical strategy.

Experience:5+ years

Skills:MentorshipCollaborationProblem-solvingAutonomyCustomer-facing communication

Tech Stack:Generative AIAgentic systemsRetrieval-Augmented Generation (RAG)LLMOpsMLOpsFine-tuningSemantic searchAWSAzureGCPSparkIcebergNiFiNVIDIA 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