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Vertex Ai Jobs (NOW HIRING)

Deloitte

Google AI Architect

San Jose, CA

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Staffingine LLC

AI/ML engineer

Los Angeles, CA · On-site

$123K - $148K/yr

Experience with Al ML search and data services within GCP ecosystem such as GCP Vertex AI Vertex AI Vector Search Gemini Cloud Run Cloud SQL etc * Experience with agent frameworks such as Google ADK ...

Deloitte

Google AI Architect

Seattle, WA

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

San Diego, CA

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Saint Louis, MO

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

San Francisco, CA

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Denver, CO

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Cleveland, OH

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Raleigh, NC

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Tempe, AZ

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

Deloitte

Google AI Architect

Jacksonville, FL

Build RAG and agentic solutions using Vertex AI Vector Search and BigQuery vector; implement context management, retrieval strategies, and observability. * Define end-to-end architectures across data ...

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How much do vertex ai jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for vertex ai in the United States is $22.50, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $24.52 per hour, depending on experience, location, and employer.

What is Vertex AI?

Vertex AI is a managed machine learning (ML) platform provided by Google Cloud that enables users to build, deploy, and scale ML models efficiently. It integrates various Google Cloud services and tools for data preparation, model training, evaluation, deployment, and monitoring, all within a unified interface. Vertex AI supports both custom and AutoML models, making it accessible for users with varying levels of ML expertise. It also offers MLOps features for workflow automation and collaboration, streamlining the entire ML lifecycle.

How do Vertex AI engineers typically collaborate with data scientists and business stakeholders on machine learning projects?

Vertex AI engineers frequently work closely with data scientists to streamline the deployment and scaling of machine learning models on Google Cloud. They help bridge the gap between model development and production, ensuring that models are robust, scalable, and aligned with business objectives. Collaboration often involves regular meetings to clarify requirements, sharing best practices for model monitoring, and integrating models with existing business systems. Effective communication skills and a clear understanding of both technical and business priorities are essential for success in this role.

What are the key skills and qualifications needed to thrive as a Vertex AI specialist, and why are they important?

To excel as a Vertex AI Specialist, you need a solid background in machine learning, data science, and cloud computing, often supported by a degree in computer science or a related field. Familiarity with Google Cloud Platform, Vertex AI tools, Python programming, and relevant certifications such as Google Professional Machine Learning Engineer are typically required. Analytical thinking, problem-solving, and strong communication skills help you collaborate with teams and explain complex AI solutions to stakeholders. These skills are vital for building, deploying, and optimizing machine learning models efficiently in cloud environments.

Does Vertex Ai have remote jobs?

Vertex AI offers remote job opportunities for roles such as data scientists and machine learning engineers. These positions often require proficiency with cloud platforms, programming skills, and collaboration tools, and may be available on a flexible or fully remote basis depending on the role and company policies.
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Vertex Ai jobs near you
Infographic showing various Vertex Ai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 21% Part Time, and 3% Contract. Highlights an 64% Physical, 4% Hybrid, and 32% Remote job distribution, with an average salary of $46,809 per year, or $22.5 per hour.

Forward Deployed Engineer (Generative AI)

Tiger Analytics Inc.

Dallas, TX • Remote

Full-time

Re-posted 8 days ago

Job description

Tiger Analytics is looking for experienced Forward Deployment Engineer (Generative AI) with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

The Forward Deployment Engineer (FDE) drives the on-site deployment, integration, and scaling of our enterprise Generative AI solutions. This role embeds directly within customer engineering teams to operationalize Large Language Models (LLMs) and retrieval systems across multi-cloud environments (AWS, Azure, GCP). You will bridge the gap between AI research and production-grade cloud infrastructure.

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

Agentic Design & Implementation
● Develop intelligent agents using Vertex AI Agent Builder to automate complex
business workflows.
● Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems
that collaborate to solve end-to-end business challenges.
● Implement tools like MCP (Model Context Protocol) Toolbox to securely connect
agents to enterprise databases like BigQuery and Spanner.


AI on Data Strategy
● Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless
integration with BigQuery for feature engineering.
● Build and optimize streaming data pipelines (e.g., via Dataflow) to execute
real-time inference using RunInference API or Vertex AI endpoints.
● Ground AI models in live business context using vector engines within BigQuery or
AlloyDB to eliminate "AI amnesia".


Operational Excellence (Soft Skills)
● Active Participation: Show up promptly for all internal and client-facing meetings.
● Transparent Communication: Provide regular, structured status updates to team
members and stakeholders regarding project milestones and technical blockers.
● Proactive Collaboration: Demonstrate the ability to ask for help when facing
technical hurdles and contribute to a collaborative troubleshooting environment.
● Consultative Approach: Navigate corporate environments to translate high-level
business goals into robust technical architectures.
Technical Qualifications
● Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and
model evaluation.
● Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML
engineering, and data preprocessing techniques (scaling, encoding, imputation).
● Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex
AI endpoints.
● Emerging Tech: Familiarity with stateful real-time processing and the latest
innovations in agentic architectures.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.