Senior Forward-Deployed AI Engineer (Remote)

Cloudera; Town of Texas (WI); Hybrid; USD 198,000 - 248,000; Full time

Benefits offered by this job

Generous PTO

Flexible WFH

Wellness programs

Phone and Internet Reimbursement

Continued Career Development

Volunteer Time

Employee Resource Groups

Job summary

Cloudera is seeking a Forward Deployed AI Engineer to embed with customers and design scalable AI/ML solutions. You will build full-stack AI applications, collaborate with customer tech and leadership teams, and drive production-ready architectures aligned to enterprise standards.

The role requires strong software, data engineering, and AI delivery skills with hands-on experience in ML systems, LLMs, and MLOps. Occasional travel and a mixed remote/on-site setup are expected.

Qualifications

• 7+ years of experience building and deploying production-grade systems, including ML
• Experience with foundation models, fine-tuning, semantic search, and agentic workflows
• Strong hands-on software engineering and data engineering skills for end-to-end AI apps

Responsibilities

• Build and prototype AI apps on Cloudera to demonstrate enterprise use cases.
• Partner with strategic customers to move AI/agentic projects from prototype to production.
• Shape enterprise AI architecture and advise on deployment and governance guidelines.
• Codify repeatable patterns into reference architectures and starter kits.
• Mentor teams and contribute reusable tooling and playbooks.

Skills

Full-stack ML engineering

ML systems deployment

LLMOps / MLOps

Customer-facing engagement

Education

BSc/MSc/PhD in related field

Tools

NVIDIA GPUs

Spark

RAG tooling

Context engineering

Job description

Cloudera is seeking a Forward Deployed AI Engineer to embed with customers and design scalable AI/ML solutions. You will build full-stack AI applications, collaborate with customer tech and leadership teams, and drive production-ready architectures aligned to enterprise standards.

The role requires strong software, data engineering, and AI delivery skills with hands-on experience in ML systems, LLMs, and MLOps. Occasional travel and a mixed remote/on-site setup are expected.