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Field Solutions Architect, GenAI, Google Cloud

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Google

15d ago

  • Job
    Full-time
    Senior Level
  • Data
    Software Engineering
  • Munich

AI generated summary

  • You need a Bachelor’s in a relevant field, 6 years in AI/ML, skills in Python and ML frameworks, and experience with Generative AI, systems design, and search concepts.
  • You will advise clients on AI-driven solutions, optimize models, create technical assets, influence strategy, and coordinate enablement activities while traveling as necessary.

Requirements

  • Minimum qualifications:
  • Bachelor's degree in Computer Science, Data Science, or equivalent practical experience.
  • 6 years of experience working in AI/ML as a technical sales engineer or in software engineering.
  • Experience in Python and Machine learning frameworks (e.g., TensorFlow, PyTorch).
  • Experience in Generative AI as a user or a developer.
  • Preferred qualifications:
  • Experience in systems design, with the ability to architect and explain data pipelines, Machine Learning (ML) pipelines, and ML training and serving approaches.
  • Experience with full-stack ML engineering to seamlessly combine retrieval-based knowledge and generative text generation to implement and optimize RAG models using first-party and OSS models.
  • Experience with implementing search concepts, such as indexing, scoring, relevancy, faceting, and query rewriting and expansion.
  • Experience with semantic search frameworks and tools/databases such as LangChain, Faiss, and Pinecone.
  • Understanding of nearest neighbors search concepts.

Responsibilities

  • Advise our customers by understanding the customer’s business process and objectives. Architect AI-drive, spanning Data, AI, and Infrastructure, and work with peers to include the full cloudstack into overall architecture.
  • Work with customers, demonstrate features, tune models, optimize model performance, profiling, and benchmarking. Troubleshoot and find solutions to issues training/serving models in a large-scale environment.
  • Build repeatable technical assets such as scripts, templates, reference architectures to enable other customers and internal teams. Work cross-functionally to influence Google Cloud strategy and product direction at the intersection of infrastructure and AI/ML by advocating for enterprise customer requirements.
  • Coordinate regional field enablement with leadership and work with product and partner organizations on external enablement activities.
  • Travel as needed.

FAQs

What are the minimum qualifications for this position?

The minimum qualifications include a Bachelor's degree in Computer Science, Data Science, or equivalent practical experience, along with 6 years of experience in AI/ML as a technical sales engineer or in software engineering, proficiency in Python and machine learning frameworks (e.g., TensorFlow, PyTorch), and experience in Generative AI as a user or developer.

What are the preferred qualifications for this role?

The preferred qualifications include experience in systems design, full-stack ML engineering, implementing search concepts such as indexing and query expansion, familiarity with semantic search frameworks and tools/databases, and understanding of nearest neighbors search concepts.

Where will this position be based?

This position can be based in Berlin, Hamburg, or Munich, Germany.

What is the primary responsibility of a Field Solutions Architect, GenAI?

The primary responsibility is to support Google Cloud Sales and Engineering teams in incubating, piloting, and deploying Google Cloud AI/ML and Generative AI technology with various customers, including AI native companies and large enterprises.

Will there be travel required in this role?

Yes, travel may be required as needed.

How does this role support customer innovation?

This role helps customers innovate faster by applying Google Cloud’s flexible and open infrastructure, including AI Accelerators (TPU/GPU), and by developing GenAI and AI/ML applications to solve problems.

What types of customers will I be working with?

You will work with AI native customers, large enterprises, and early-stage AI startups.

What types of technical assets are expected to be built in this role?

You are expected to build repeatable technical assets such as scripts, templates, and reference architectures to enable other customers and internal teams.

What kind of support will I provide to customers?

You will advise customers by understanding their business processes and objectives, demonstrating features, tuning models, optimizing performance, and troubleshooting issues related to training and serving models in a large-scale environment.

Is Google committed to diversity and inclusion in the workplace?

Yes, Google is proud to be an equal opportunity workplace and an affirmative action employer, committed to equal employment opportunity regardless of various characteristics such as race, gender identity, and disability.

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Google

Technology
Industry
10,001+
Employees
1998
Founded Year

Mission & Purpose

A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.