Solutions Engineer Job at Cloudera

Solutions Engineer

Cloudera

Location:
Malaysia

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Not provided

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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 Solutions Engineer at Cloudera, your mission is to remove technical barriers and accelerate adoption of Cloudera’s data and AI platform. You’ll partner with customers to architect enterprise-scale solutions that span data ingestion, transformation, governance, and machine learning — including emerging use cases around Generative AI. This is not a PowerPoint-only role. You’ll be a practitioner-architect working directly with enterprise data teams, ML engineers, and IT architects to design and implement real-world solutions, including MLOps pipelines, AI/ML workflows, and production-grade GenAI use cases.

Job Responsibility:

Collaborate with customers, partners, and prospects to understand business and technical requirements, and design data and AI solutions using Cloudera technologies
Architect end-to-end machine learning pipelines from data ingestion to model deployment and monitoring
Lead technical conversations around MLOps, data science workflows, and GenAI integration with enterprise platforms
Own the technical sales process from introduction through post-sales success, including expansion and renewal
Deliver demos, whiteboarding sessions, and proof-of-concepts that showcase real-world value
Evangelize Cloudera’s AI and data platform vision to data scientists, ML engineers, and business stakeholders
Work closely with Account Executives to drive customer success and strategic growth
Collaborate cross-functionally with Product, R&D, Marketing, and Customer Success teams

Requirements:

Minimum 5 years of experience in a customer-facing technical role
A Bachelor’s degree or higher in Computer Science, Engineering, or a related field
Strong hands-on experience as an AI/ML practitioner — including model development, deployment, and lifecycle management
Proven ability to design and deploy MLOps pipelines (training, CI/CD, monitoring, retraining)
Experience working with GenAI models and frameworks (e.g., LLM orchestration, prompt engineering, RAG pipelines)
Excellent communication skills with the ability to explain technical AI concepts to both technical and business audiences
Fluent in Malay and English (spoken and written)
Solid understanding of machine learning, MLOps, and data science best practices
Experience with frameworks such as MLflow, Kubeflow, Airflow, or Cloudera AI

Nice to have:

Experience building or deploying Generative AI applications (e.g., chatbots, document summarization, code generation)
Knowledge of RAG (Retrieval Augmented Generation) and LLM fine-tuning techniques
Experience with Cloudera or similar enterprise data stacks
Public cloud certifications (AWS, Azure, GCP) or Cloudera certifications
Familiarity with security, governance, and data lineage tools and practices
Previous experience with enterprise data platforms such as Databricks, Snowflake, or Confluent
Hands-on with Python, Jupyter Notebooks, and popular ML libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch)
Familiarity with GenAI toolkits (e.g., LangChain, LlamaIndex, Hugging Face Transformers)
Experience with cloud-based AI workloads on AWS, Azure, or GCP
Knowledge of data engineering and pipeline orchestration tools: Spark, Kafka, Flink, Hive, Impala
Strong Unix/Linux background and basic understanding of DevOps and containerization (Docker, Kubernetes)

Additional Information:

Job Posted:
January 31, 2026

Employment Type:

Fulltime

Work Type:

Remote work

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