Senior Solutions Engineer

• Own the technical sales process from introductory net-new-sales meetings through post-sales customer satisfaction, upselling, and subscription renewals
• Support customers by discovering use cases for Cloudera technology, especially Generative AI, predictive analytics, and enterprise MLOps
• Design customer solutions using Cloudera technologies, reference architectures, and common patterns such as Open Data Lakehouse, RAG, and end-to-end ML pipelines
• Demonstrate Cloudera products, including data engineering pipelines, model training/deployment workflows, and Generative AI features
• Partner with Account Managers to communicate the business and technical value of Cloudera solutions and drive sales
• Present product roadmap and vision, including AI capabilities, hybrid MLOps, and secure data access
• Interface with Cloudera teams to provide a consistent customer experience
• Advocate customer needs to Product Management and Engineering
• Participate in conferences, meetups, webinars, blogs, and other external evangelism
• Achieve annual sales expectations aligned to a team target
• Participate in knowledge exchange with peers and the wider community

• Minimum of 8 years of experience in a customer-facing role, ideally in a pre-sales context focused on big data platforms, enterprise software, or advanced analytics platforms
• Ability to create and give technical presentations and demonstrations translating complex data and AI concepts into strategic business value
• Experience with Big Data, Data Warehousing, or Relational Databases, including Apache Iceberg, Apache Spark, Hive, or the Hadoop ecosystem
• Hands-on experience building, integrating, and deploying AI solutions using PyTorch, Hugging Face, LangChain/LlamaIndex, vector databases, and MLOps tooling
• Deep understanding of Generative AI architectures, including RAG, fine-tuning, and model serving
• Experience with AWS, Azure, or GCP
• Experience with enterprise operations, security, and data governance, including data privacy, compliance, and AI model/data asset governance
• Experience with Unix or Linux environments and shell scripting
• Experience gathering and understanding customer business requirements across traditional data engineering and modern AI applications
• Excellent written and verbal communication skills
• Strong problem-solving skills and an analytical mindset
• Four-year degree (Bachelor's) from an accredited university required; Computer Science, Data Science, Engineering, or related quantitative field preferred
• Ability to travel domestically and internationally

• Generous PTO Policy
• Unplugged Days supporting work-life balance
• 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