_{11th February, 2025}

About the job: 
Title – Practice Leader AI/ Data-Energy and Manufacturing
Start date: Immediate 
Position Type: Full-Time Employment 
Location: Remote across North America 
  
Overview 
We are seeking an experienced Practice Leader AI/ Data with a strong background in AI/ML technologies, Data Engineering, and a deep understanding of the Energy and Manufacturing sectors. The role is particularly focused on the Manufacturing and Oil and Gas with good understanding of Midstream segment but is not limited to it. This role requires expertise in data pipelines, ETL processes, and working with cloud platforms (Azure, AWS, GCP). The ideal candidate will also have experience in AI/ML tools and technologies applied to both predictive maintenance, energy optimization, and smart manufacturing solutions. The candidate will work in a client-facing capacity, engaging with energy and manufacturing clients to design AI solutions. You will lead the design of AI models while ensuring the implementation of secure, compliant, and efficient solutions. 
  
Key Responsibilities 
  

• AI/ML Solution Architecture: Lead the design and development of scalable AI architectures and systems for the Energy and Manufacturing sectors. This includes implementing AI solutions for predictive maintenance, asset optimization, energy usage optimization, demand forecasting, and smart manufacturing. Hands-on experience is required to build prototypes and demonstrate the models for the client. 
• Client Interaction: Serve as a trusted advisor to Energy and Manufacturing clients by understanding their unique operational challenges. Work closely with them to design tailored AI solutions that drive business value. You will communicate technical concepts to both technical and non-technical stakeholders, ensuring alignment with the client’s strategic goals and business needs. 
• Data Engineering & Integration: Lead the development and optimization of data pipelines and ETL processes for Energy and Manufacturing data using Azure, AWS, and GCP. Ensure seamless integration of complex data sources, such as sensor data, SCADA systems, IoT devices, production data, and sensor data into AI models and systems. 
• Security and Compliance: Ensure that all AI-driven solutions comply with the data security standards and regulatory requirements specific to Energy and Manufacturing industries. Lead efforts to ensure sensitive data is handled securely and that AI solutions comply with relevant industry regulations (e.g., ISO 50001, NERC CIP, GDPR). 
• Innovation and Research: Stay up-to-date with the latest developments in AI/ML technologies, particularly in Energy and Manufacturing. Continuously identify opportunities to apply emerging technologies to solve key business challenges, such as real-time monitoring, asset management, energy optimization, and advanced manufacturing processes. 
• Collaboration with Cross-functional Teams: Collaborate with energy professionals, product managers, engineers, and other business stakeholders to ensure AI solutions are aligned with operational goals and deliver meaningful outcomes. Foster a collaborative environment to ensure AI projects are executed effectively. 

  
  Required Skills and Qualifications 

Education: 

• Master’s degree in Computer Science, Artificial Intelligence, Data Engineering, Energy Management, or a related field. 
• A Ph.D. in AI/ML, Data Science, or Energy Engineering is a plus. 

  Experience: 

• 10+ years in AI/ML architecture, Data Engineering, and building data pipelines. 
• Proven experience working with cloud platforms (Azure, AWS, GCP) and modern AI/ML tools and technologies. 
• Energy & Manufacturing Expertise: Strong knowledge of Oil & Gas (especially Midstream), manufacturing processes, and experience working with industry-specific data sources (e.g., sensor data, SCADA, IoT, production data). 
• In-depth understanding of industry regulations and data security standards (e.g., ISO 50001, GDPR, NERC CIP) and experience ensuring compliance in data handling and model development. 

  AI/ML Technologies: 

• Hands-on expertise in predictive maintenance, energy optimization, asset management, and other AI/ML frameworks like TensorFlow, PyTorch, scikit-learn, Keras. 
• Familiarity with IoT data, sensor-based analytics, and applications like demand forecasting and real-time monitoring in Energy and Manufacturing. 

  Cloud and Data Engineering: 

• Expertise in building and deploying data pipelines and ETL processes in cloud environments (Azure, AWS, GCP). 
• Familiarity with DataBricks, Apache Spark, and other big data technologies is highly desirable. 

  Client-Facing Skills: 

• Strong interpersonal and communication skills, with a proven ability to effectively communicate complex technical concepts to both technical and non-technical audiences. 
• Comfortable presenting solutions to C-level executives and working directly with clients to define business requirements. 

  Leadership: 

• Proven ability to lead cross-functional teams and mentor junior team members. 
• Experience creating a collaborative, innovative, and results-driven working environment. 

  
Preferred Qualifications 

• PhD in AI/ML, Energy Engineering, Industrial Engineering, or related fields. 
• Certifications in cloud platforms (e.g., AWS Certified Machine Learning, Google Professional Data Engineer). 
• Experience building AI solutions for predictive maintenance, asset management, and other Energy and Manufacturing-specific domains. 

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