[Hiring] Forward Deployed AI Engineer @Cloudera

Role Description

At Cloudera, we empower people to transform complex data into clear and actionable insights. With as much data under management as the hyperscalers, we're the preferred data partner for the top companies in almost every industry. Powered by the relentless innovation of the open source community, Cloudera advances digital transformation for the world’s largest enterprises.

Cloudera’s Forward Deployed Engineering (FDE) function sits within the Applied AI organization and is a specialized AI/ML engineering team focused on accelerating AI adoption within our most strategic enterprise customers. We embed directly with customers to rapidly pilot AI use cases, solve real-world business challenges, and help operationalize advanced AI capabilities within enterprise environments.

Cloudera FDEs operate at the intersection of customer engineering, AI innovation, and enterprise deployment—driving high-impact AI outcomes for customers and codifying solution patterns for repeatable delivery at scale.

We are looking for a seasoned, full-stack ML engineer who can embed with customers to design technical use cases and ship scalable enterprise AI/ML solutions on the Cloudera platform.

As a Forward Deployed AI Engineer you will:

• Develop full-stack AI/ML applications on Cloudera to demonstrate how AI and agentic systems solve real enterprise use cases.
• Work directly with customer teams to drive AI and agentic use cases from early prototype toward production readiness.
• Advise customer leaders on AI roadmaps, solution design, deployment, and AI use cases.
• Standardize successful patterns into repeatable reference architectures, productized solutions, starter kits, and internal playbooks.
• Act as a thought leader, mentor Cloudera teams, and contribute to resources that grow our overall AI capability.
• Channel field and customer feedback back to Product teams to continuously improve our AI platform and products.

Qualifications

• 7+ years of experience building and deploying production-grade systems.
• 2–4 years of experience specifically focused on building ML systems or GenAI and agentic applications.
• Strong hands-on software engineering, data engineering, and applied AI/ML skills.
• Demonstrated experience building full-stack ML applications or agentic systems using modern AI frameworks and tooling.

Requirements

• Experience with MLOps frameworks, LLM orchestration, and modern AI stacks (e.g., LangChain, LlamaIndex, vLLM, Ray, MLflow).
• Hands-on experience with Vector Databases and Retrieval-Augmented Generation (RAG) architectures.
• Background in client-facing consulting, technical account management, or solution architecture within enterprise environments.
• Familiarity with distributed data engineering platforms (Apache Spark, Iceberg, Kubernetes).

Benefits

• Generous PTO Policy
• Support work life balance with Unplugged Days
• Flexible WFH Policy
• Mental & Physical Wellness programs
• Phone and Internet Reimbursement program
• Access to Continued Career Development
• Comprehensive Benefits and Competitive Packages
• Paid Volunteer Time
• Employee Resource Groups