Business Area:
Professional ServicesSeniority 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.
Role Overview
At Cloudera, you will bridge the gap between complex data technologies and actionable learning. You will design and develop hands-on technical training, workshops, and certification content focused on Generative AI Applications, Agentic AI, MLOps, and modern Data Engineering for customers, partners, and internal teams.
As a Senior Technical Curriculum Developer You will:
Design and develop technical training focused on Generative AI, Agentic AI workflows, and AI application development including the NVIDIA AI Agent stack.
Create instructor-led guides, lab manuals, Jupyter notebook-based exercises, and on-demand video content.
Develop technical assessments, certification questions, and demo environments.
Develop real-world AI agents and data scenarios across Banking, Telecom, Retail, Healthcare, and other enterprise domains.
Workshop Delivery & Technical Integration
Lead and conduct technical ML/AI and Agent development workshops directly for customers and internal teams.
Build and maintain labs using Python, AI/ML frameworks, Vector databases, and NVIDIA-accelerated data pipelines (e.g., cuDF, Apache Spark on GPUs).
Partner with Product, Engineering, and Solution Architecture teams to ensure training reflects the latest platform capabilities.
Continuous Improvement
Iterate on course content based on learner feedback, instructor input, and emerging industry trends like LLMOps.
Support internal enablement initiatives and maintain technical walkthroughs.
We’re excited about you if you have:
Python, React, Node.js, HTML, and Markdown.
Data & Infrastructure: SQL, Linux, Bash scripting, Kubernetes, and Docker.
Traditional ML (PyTorch or similar), Generative AI, and building enterprise Agentic AI workflows. Familiar with OpenAI v1 API and how to build with it.
Experience with the NVIDIA AI Agent & Data Engineering stack, including NVIDIA NIM, NeMo Retriever, NeMo Guardrails, and cuDF for accelerated data processing.
AI Coding agents (Cursor, Claude, Codex, Gemini) and modern IDEs.
Experience & Competencies:
Total 6+ years of data and application development experience with 4+ years in curriculum development, technical training, AI/ML/Data Engineering, or MLOps.
Proven ability to conduct hands-on workshops and simplify complex AI concepts for technical and non-technical audiences.
Expertise in Agent frameworks (CrewAI, LangChain, NVIDIA AI-Q), Vector databases, RAG pipelines, and Git/version control.
You may also have:
Advanced Architecture Knowledge of Data Lakehouse architectures, Apache Spark, Kafka, and Airflow.
Governance Familiarity with AI governance, Responsible AI, and NVIDIA OpenShell for secure agent runtimes.
Platform & Operations Exposure to Cloudera environments, LMS platforms, and DevOps/CI/CD practices.
Multimedia Experience with certification development and video recording/editing tools.
What you can expect from us:
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
Employee Resource Groups
EEO/VEVRAA
#LI-Remote
#LI-VG1
Based on 639 disclosed AI Engineering salaries on RoleSuite, the role pays a median of $201K/year, with most offers between $162K and $246K (10th–90th percentile: $131K–$286K).
See the full AI Engineering salary breakdown →