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Presales Solutions Engineer

India, Bangalore · Job Posted February 14, 2026
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Job 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. As a Presales Solution Engineer, you will partner and collaborate with the sales team to design, present, and prove Cloudera’s hybrid data platform and AI/ML solutions to end customers. This role requires deep technical expertise, hands-on development skills, and the ability to translate complex concepts into clear, compelling business value for enterprise customers.

Job Responsibility

  • Lead discovery sessions with enterprise customers to understand business objectives and technical requirements
  • Deliver impactful presentations, whiteboard sessions, and product demonstrations
  • Drive proof-of-concept (POC) projects, including setup, data integration, and performance validation
  • Architect end-to-end data pipelines and AI/ML workflows using Cloudera Data Platform (CDP) across on-prem, hybrid, and public cloud deployments
  • Design scalable solutions covering data ingestion, streaming, data lakes/warehouses, and machine-learning lifecycle management
  • Recommend cluster sizing, performance tuning, and security/governance best practices
  • Build and deploy ML models using Python, Scala, or Java with frameworks such as PyTorch, TensorFlow, or Spark MLlib
  • Develop reproducible pipelines for model training, testing, and deployment (MLflow, Kubeflow, or equivalent)
  • Collaborate with customer data science teams to accelerate the adoption of Cloudera Artificial Intelligence (CAI) and Agentic workflows ecosystems
  • Create reusable demo assets, sample code, and reference architectures highlighting AI/ML capabilities
  • Demonstrate Cloudera best practices and/or AI/ML integration patterns
  • Represent Cloudera at industry conferences, webinars, and community events

Requirements

  • 10+ years in data engineering, AI/ML engineering, or solution architecture
  • At least 1 year in a customer-facing pre-sales or consulting capacity
  • Experience with GenAI or LLM-based solutions
  • Strong coding ability in Python, prompt engineering, SQL, RDBMS, and at least one additional language (Java/Scala preferred)
  • Deep knowledge of distributed data systems (Hadoop, Spark, Kafka, Iceberg) and major cloud platforms (AWS, Azure, GCP)
  • Hands-on experience building, training, and deploying machine learning models in production
  • Exceptional presentation and storytelling skills
  • Ability to deliver crisp presentations and documentation with well-structured arguments

Nice to have

  • Experience with containerization and orchestration (Docker, Kubernetes)
  • Familiarity with MLOps practices, CI/CD pipelines, and model monitoring
  • Understanding of data security, governance, and compliance frameworks (GDPR, HIPAA, etc.)
  • Ability to connect customer goals with Cloudera’s platform vision

What we offer

  • 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

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  • Strong communication and presentation skills, with the ability to explain complex technical concepts to both technical and non-technical audiences
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  • Partner closely with the Sales team to introduce Global-e’s cross-border solution to prospective customers
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  • drive proof-of-concept (POC) projects, including setup, data integration, and performance validation
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  • collaborate with customer data science teams to accelerate the adoption of Cloudera Artificial Intelligence (CAI) and Agentic workflows ecosystems
  • create reusable demo assets, sample code, and reference architectures highlighting AI/ML capabilities
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  • recommend cluster sizing, performance tuning, and security/governance best practices
  • build and deploy ML models using Python, Scala, or Java with frameworks such as PyTorch, TensorFlow, or Spark MLlib
  • develop reproducible pipelines for model training, testing, and deployment (MLflow, Kubeflow, or equivalent)
  • collaborate with customer data science teams to accelerate the adoption of Cloudera Artificial Intelligence (CAI) and Agentic workflows ecosystems
  • create reusable demo assets, sample code, and reference architectures highlighting AI/ML capabilities
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  • Generous PTO Policy
  • support work life balance with Unplugged Days
  • flexible WFH Policy
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