Customer Engineer, Data Analytics and Artificial Intelligence

3 Months ago • 10 Years + • Artificial Intelligence

Job Summary

Job Description

As a Customer Engineer, you'll partner with Google Cloud's technical sales teams, acting as a subject matter expert in data, AI, and ML. You'll help customers understand Google Cloud, develop cloud solutions, conduct proof-of-concepts, and troubleshoot technical issues. Responsibilities include identifying business opportunities, sharing data analytics expertise, architecting client solutions, demonstrating product integrations, and delivering business presentations. You'll work directly with customers, internal engineering teams, and product management to improve products and solutions, optimizing for results and identifying innovative ways to increase impact. The role requires strong technical, communication, and organizational skills.
Must have:
  • Bachelor's degree in computer science or equivalent experience
  • 10+ years cloud native architecture experience (customer-facing)
  • Big Data technologies expertise (analytics, processing, transformation)
  • ML model development & deployment experience (PyTorch, TensorFlow, etc.)
  • Experience presenting to technical and executive stakeholders
Good to have:
  • Cloud computing experience (infrastructure, storage, platforms)
  • Technical sales or consulting experience in cloud, data analytics, or AI/ML
  • Experience with data and information management in big data contexts
  • Experience architecting/developing software for scalable, distributed systems
  • Experience building ML solutions and leveraging specific ML architectures
  • Understanding customer requirements and designing technical architectures

Job Details


Minimum qualifications:

  • Bachelor's degree in computer science or equivalent practical experience.
  • 10 years of experience with cloud native architecture in a customer-facing or support role.
  • Experience with "Big Data" technologies or concepts, such as analytics warehousing, data processing, data transformation, data governance, data migrations, ETL, ELT, SQL, NoSQL, and other data concepts.
  • Experience with Machine Learning model development and deployment frameworks for deep learning (e.g. PyTorch, Tensorflow, Jax, Ray, etc.), AI accelerators (e.g. TPUs, GPUs), model architectures (e.g. encoders, decoders, transformers), and using machine learning APIs.
  • Experience working with, and presenting to, technical stakeholders and executive leaders.

Preferred qualifications:

  • Experience with aspects of cloud computing (infrastructure, storage, platforms and data), as well as the cloud market, competitive dynamics and customer buying behavior.
  • Experience in technical sales or consulting in cloud computing, data analytics, Big Data, or AI/ML.
  • Experience in data and information management as it relates to big data trends and issues within businesses.
  • Experience in architecting and developing software or infrastructure for scalable, distributed systems.
  • Experience in building Machine Learning solutions and leveraging specific Machine Learning architectures.
  • Experience in understanding customer requirements with the ability to break down requirements and design technical architectures.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Data, and Artificial Intelligence and Machine Learning (AI/ML) to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners in understanding Google Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs of concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers in understanding the business and technical requirements, and present practical and useful solutions on Google Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply your impact and the impact of the team as a whole.

Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

Responsibilities

  • Work with the team to identify and qualify business opportunities, understanding key customer technical objections, and develop the strategy to resolve technical blockers.
  • Share in-depth data analytics expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
  • Identify business and technical requirements, conduct full technical discovery and architect client solutions to meet gathered requirements.
  • Work directly with Google Cloud products to demonstrate and prototype integrations in customer and partner environments.
  • Prepare and deliver business messages in an effort to highlight the Google Cloud value proposition, using techniques such as whiteboard and slide presentations, product demonstrations, white papers and Request for Information (RIF) responses.

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