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 pilot and productionize AI and agentic applications. Build full-stack AI apps on the Cloudera platform, partner from prototype to readiness, and advise on AI roadmaps and deployment considerations. Standardize successful delivery into repeatable architectures and playbooks while mentoring internal teams. Continuously feed customer and field signals back to Product teams to improve the AI platform.

Location: Austin

Workplace: Hybrid

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 solve real enterprise use cases.
•Work directly with customer teams to move 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 successful solution patterns into reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, grow AI capability resources, and channel customer signal back to Product teams.

Pay and Benefits

Perks:Paid LeaveRemote Work

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 to build full-stack AI applications or agentic systems.
•Experience with foundation models and LLM application techniques including context engineering, fine-tuning, semantic search, RAG, and agentic workflows.
•Deep understanding of LLMOps/MLOps practices (evaluation, observability, serving, monitoring, and lifecycle management).
•Experience designing scalable enterprise AI architectures aligned to security, governance, and compliance standards.

Experience:SaaSEnterprise software

Skills:MentorshipCollaborationCustomer communicationHigh agencyAutonomous execution

Tech Stack:AWSAzureGCPSparkIcebergNiFiNVIDIA 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: 13 hours agoStatus: Live

Job Summary

Location: Austin

Workplace: Hybrid

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 solve real enterprise use cases.
•Work directly with customer teams to move 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 successful solution patterns into reference architectures, productized solutions, starter kits, and internal playbooks.
•Mentor Cloudera teams, grow AI capability resources, and channel customer signal back to Product teams.

Pay and Benefits

Perks:Paid LeaveRemote Work

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 to build full-stack AI applications or agentic systems.
•Experience with foundation models and LLM application techniques including context engineering, fine-tuning, semantic search, RAG, and agentic workflows.
•Deep understanding of LLMOps/MLOps practices (evaluation, observability, serving, monitoring, and lifecycle management).
•Experience designing scalable enterprise AI architectures aligned to security, governance, and compliance standards.

Experience:SaaSEnterprise software

Skills:MentorshipCollaborationCustomer communicationHigh agencyAutonomous execution

Tech Stack:AWSAzureGCPSparkIcebergNiFiNVIDIA 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