Senior Technical Solutions Consultant, Applied AI, Google Cloud
Job Summary
Job Description
- Bachelor's degree or equivalent experience
- 5+ years project management and solution delivery experience
- Experience with all phases of ML project delivery
- Technical client service experience
- Experience building solutions with Generative AI
- 5+ years experience with enterprise and cloud systems
- Experience with image generation and multimodal deep learning
- Experience with prompt engineering and LLM evaluation
- Experience with ML Operations frameworks (Kubeflow, MLFlow, Vertex AI Pipelines)
- Public speaking and presentation experience
5 skills required
Job Details
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience project managing and delivering technical solutions.
- Experience with all phases of a Machine Learning project delivery from data collection to production deployment at scale.
- Experience with technical client service (e.g., consulting).
- Experience building solutions with Generative AI technologies.
Preferred qualifications:
- 5 years of experience working directly with enterprise and cloud technology systems, designing solutions, or developing business applications.
- Experience with image generation and multimodal deep learning/foundational models and understanding of NLU, and conversational design principles.
- Experience working with prompt engineering and LLM evaluation benchmarks and agentic workflows.
- Experience with ML Operations frameworks such as Kubeflow, MLFlow, Vertex AI Pipelines, and running training and prediction jobs at scale.
- Experience with public speaking such as facilitating customer workshops or presenting at industry events.
- Excellent communication, writing, presentation, and problem-solving skills.
About the job
As a member of the Applied AI Engineering team, you will help customers discover use cases for and better understand the potential GenAI. You'll scale your impact through publishing best practices, demos, and tutorials, and developing code-samples that customers can use to deploy. You will provide direction on how to tailor the mechanisms used to deploy workloads at scale reliably and securely to production and apply Responsible AI principles.
You will communicate with businesses of all types to help them adopt Google products and solutions wherever they are on their AI journey. You will explore and experiment with our suite of products, partner tools, and third-party applications to build and deploy cloud solutions.
The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
The US base salary range for this full-time position is $147,000-$216,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about .
Responsibilities
- Partner closely with Technical Solutions Management and drive alignment with Product and Engineering to build the most innovative solutions leveraging Generative AI.
- Collaborate closely with cross-functional teams and help scale technical assets such as benchmarks and best practices.
- Work as part of a broader Applied AI Engineering team to contribute technical assets, prioritize and shape solution direction, while impacting top line business and bookings.
- Drive complex technical projects and ensure high-quality solutions.
- Oversee and guide, as necessary, customer engagements of the team.
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About The Company
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.
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