Client-Facing Enterprise AI Engineer

Cloudera; New York (NY); Hybrid; USD 198,000 - 248,000; Full time

Benefits offered by this job

Generous PTO Policy

Flexible WFH policy

Wellness programs

Comprehensive benefits

Job summary

Cloudera is seeking a seasoned Forward Deployed AI Engineer to embed with enterprise customers and design scalable AI/ML solutions. You will build full-stack AI apps, collaborate with customer teams, and guide architecture decisions to production readiness.

Ideal candidates have 7+ years in production-grade systems plus 2–4 years in ML or GenAI, with strong software/data engineering and MLOps expertise. Strong communication with technical and executive audiences is essential.

Qualifications

• 7+ years building and deploying production-grade systems
• 2–4 years building ML systems or GenAI/agentic apps
• Strong hands-on software engineering and data engineering
• Experience with foundation models, fine-tuning, semantic search, and RAG
• LLMOps, evaluation, observability, serving, monitoring and lifecycle management
• Ability to translate customer needs into technical strategy

Responsibilities

• Build and prototype AI/ML apps on Cloudera platform
• Partner with strategic customers to move from prototype to production
• Shape enterprise AI architecture aligned to security and governance
• Codify reusable AI patterns into reference architectures
• Mentor teams and contribute to reusable tooling and playbooks

Skills

Full-stack ML engineering

Data engineering

Applied AI/ML

LLMOps / MLOps

Foundation models & RAG

Agentic AI / autonomous systems

Customer engagement

Education

BSc/MSc/PhD in related field

Tools

NVIDIA GPUs

Cloud platforms (AWS/Azure/GCP)

Job description

Cloudera is seeking a seasoned Forward Deployed AI Engineer to embed with enterprise customers and design scalable AI/ML solutions. You will build full-stack AI apps, collaborate with customer teams, and guide architecture decisions to production readiness.

Ideal candidates have 7+ years in production-grade systems plus 2–4 years in ML or GenAI, with strong software/data engineering and MLOps expertise. Strong communication with technical and executive audiences is essential.