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Solutions Engineer – Artificial Intelligence

Cloudera · Singapore

Singapore · On-siteFull-TimePosted Jun 17, 2026

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Job description

Business Area:

Sales EngineeringSeniority Level:

Mid-Senior levelJob 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.

About Cloudera

We are on a mission to make data and analytics easy and accessible to everyone. The work we do empowers any organization—from the world's largest enterprises to small nonprofits—to use data to solve some of the most complex challenges that impact businesses, communities, and lives.

At Cloudera, we are Customer Driven & People First. We believe in the power of our people because when we bring together bold ideas, collaboration, and purpose, we do not just imagine the future—we help build it.

The Role

This position will serve as a customer-facing, hands-on technologist with a track record of success. You will be the technical authority for Cloudera’s Enterprise AI portfolio, bridging the gap between complex data architectures and actionable AI business outcomes.

In this senior individual contributor role, you will own the technical sales strategy for the industry’s only platform bringing AI to data anywhere. You will not only demonstrate technology but also inspire customers to think bigger about their AI roadmap, ensuring they understand the value of the Open Data Lakehouse and Unified Data Fabric.

As a Solutions Engineer – Artificial Intelligence, you will:

  • Innovation Lifecycle - develop advanced techniques, solutions, and methodologies for customer core business process adoption
  • Research Engineering - assist domain experts, scientists, data scientists and technical engineers to develop AI Solutions to meet organizational objectives to include
  • Computational Engineering - work with clients to define objectives to curate data, algorithms, and outcomes; setup training pipelines, large-scale customer experiments, and evaluate models for production deployment
  • Research Consultation - consult with research scientists on the art of the possible and invention of new theoretical ideas, and or the practical application of theories to drive a computational engineering solution pipeline
  • Own the Technical Sales Lifecycle: Drive the technical sales process from introductory meetings and discovery through to post-sales success, upselling, and subscription renewals.
  • Architect AI Solutions: Design comprehensive solutions for customer needs using Cloudera technologies—specifically Cloudera AI, AI Inference, AI Studios, and AI Workbench—based on reference architectures and common patterns.
  • Strategic Evangelism: Present Cloudera’s product roadmap and vision to C-level executives (CIO, CTO, CDO), demonstrating how AI Agents and Cloud Bursting accelerate enterprise AI adoption.
  • Demonstrate Value: Create and deliver inspiring technical presentations and demonstrations that compel customers to say “yes” to Cloudera. Partner with Account Managers to articulate the true business value of our solutions.
  • Voice of the Customer: Interface with Product Management and Engineering to advocate for your customers' needs, transforming feedback from the field into actionable roadmap items.
  • Community Leadership: Participate in external publicity and evangelism, including speaking at conferences, writing blogs, and leading webinars to drive the narrative around trusted Enterprise AI.

We’re excited about you if you have:

  • Senior Experience: A minimum of 8 years of experience in a customer-facing role, ideally in a pre-sales or solutions engineering context.
  • AI & Data Proficiency: Deep experience with Data Engineering, Data Science, or Machine Learning. You understand the difference between Data Engineering and Data Science a

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