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Global Director, AI Industry Solutions - Energy

Remote / Online - Candidates ideally in
Wisconsin, USA
Listing for: Cloudera
Full Time, Remote/Work from Home position
Listed on 2026-03-01
Job specializations:
  • IT/Tech
    AI Engineer, Data Science Manager, Machine Learning/ ML Engineer, Data Scientist
Salary/Wage Range or Industry Benchmark: 150000 - 200000 USD Yearly USD 150000.00 200000.00 YEAR
Job Description & How to Apply Below
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Remote locations:
US-Texas-Remote time type:
Full time posted on:
Posted Todayjob requisition :
260237
** Business Area:
** Corp. Strategy
** Seniority Level:
** Director
*
* 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.

We are looking for a
** Global Director, AI Industry Solutions
** focused on the Energy sector (oil & gas, utilities, power generation, renewables, and energy trading). This is a deeply technical, customer-facing leadership role demanding hands-on AI fluency — the ability to architect solutions, guide model operationalization, and credibly engage data science and engineering leaders within our largest energy accounts.

You will translate Cloudera's AI platform capabilities — including Cloudera AI Workbench, AI Registry, our Enterprise AI Ecosystem, and agentic AI frameworks — into production-grade, industry-specific solutions that solve real business problems at scale across the energy value chain.
** As Global Director, AI Industry Solutions you will:
*** Develop and own the global AI industry solutions strategy for Energy — including AI business plans, solution playbooks, and technical reference architectures mapping Cloudera's platform to high-value energy use cases (predictive asset maintenance, grid optimization, reservoir modeling, drilling optimization, energy trading analytics, demand forecasting, emissions monitoring, SCADA/IoT data analytics, renewable generation forecasting, and safety/compliance automation).
* Lead hands-on AI solutioning with strategic energy customers, designing end-to-end architectures spanning real-time IoT data ingestion, sensor data processing, feature engineering, model training, RAG pipelines, fine-tuning, model serving, and governance on the Cloudera platform.
* Serve as the primary AI technical authority for Energy — able to credibly discuss ML/AI workflows, LLM orchestration, agentic AI patterns, time-series modeling, digital twin architectures, and operational AI with customer CDOs, CTOs, Chief Digital Officers, and ML engineering teams.
* Collaborate with Product, Engineering, and the Cloudera AI team to influence the AI product roadmap based on energy customer requirements — particularly around edge-to-cloud data architectures, real-time streaming analytics, and OT/IT data convergence.
* Work with Enterprise AI Ecosystem partners (NVIDIA, Anthropic, AWS, Pinecone, and others) to co-develop integrated energy solutions and joint go-to-market motions.
* Build and publish AI Accelerators (AMPs) and solution blueprints enabling rapid deployment of energy-specific AI use cases.
* Provide deep technical AI support during strategic sales cycles — whiteboarding architectures, leading proof-of-concept design, and guiding executive-level AI strategy discussions with energy majors and utilities.
* Develop thought leadership including technical blogs, conference presentations, and solution demos positioning Cloudera as the enterprise AI platform of choice for energy.
* Represent Cloudera at key energy industry forums .
** We are excited about you if:
*** A minimum of 10+ years of experience in AI/ML, data & analytics, or enterprise software, with significant experience in oil & gas, utilities, power generation, renewables, or energy trading.
* Bachelor's degree in Computer Science, Engineering, Data Science, or related quantitative field;
Master's or MBA preferred.
* Deep hands-on fluency with AI/ML technologies — ability to discuss model architectures, training pipelines, inference optimization, and production ML systems with authority.
* Experience working with energy enterprises on AI transformation, data modernization, OT/IT data…
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