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Google Ai Engineer Jobs (NOW HIRING)

Sincera Technologies, Inc.

AI Engineer

Jersey City, NJ · On-site

$109K - $149K/yr

Senior AI Engineer Google AI & Generative Intelligence Location: [Paramus, NJ / Hybrid] Experience Required: 10 15 Years in Software Engineering | 5+ Years in Artificial Generative Intelligence We ...

Qaurs Techno Systems LLC

AI Engineer

Charlotte, NC · On-site

$50K - $60K/yr

Utilize Google ADK (AI Developer Kits) and related Google Cloud AI services (e.g., Vertex AI ... Gemini APIs) to deploy robust AI solutions. * Cross-Functional Collaboration: Work closely with ...

SHI

Solutions Engineer - Google AI

Austin, TX

Job Summary The Solutions Engineer - Google AI collaborates with account and specialty teams to assess customer cybersecurity needs. They will be a customer-facing cloud AI expert.They will take a ...

Deloitte

Google AI Lead Architect

San Antonio, TX

$49.75 - $68.25/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Austin, TX

$54.75 - $75/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Pittsburgh, PA

$53.75 - $73.50/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Baltimore, MD

$55 - $75.25/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Indianapolis, IN

$52.75 - $72.50/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Boston, MA

$60 - $82.25/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Charlotte, NC

$54 - $74/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Miami, FL

$52.75 - $72.50/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

Deloitte

Google AI Lead Architect

Saint Louis, MO

$53.75 - $73.75/hr

Join our AI & Engineering team in transforming technology platforms, driving innovation, and helping make a significant impact on our clients' success. You'll work alongside talented professionals ...

PGTEK

Lead Cloud AI Engineer - Travel role

Washington, DC · On-site

$120K - $150K/yr

As we expand our Google Cloud and AI practice, we're seeking a Lead Cloud AI Engineer to serve as the senior technical authority for enterprise cloud migration and AI platform modernization ...

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All JobsGoogle Ai Engineer Jobs

Google Ai Engineer information

See salary details

$39K

$101.8K

$137.5K

How much do google ai engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for google ai engineer in the United States is $101,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $116,500.00 per year, depending on experience, location, and employer.

What are Google AI Engineers?

Google AI Engineers are professionals who design, develop, and implement artificial intelligence and machine learning solutions at Google. They work on a wide range of projects, from improving search algorithms to developing intelligent systems for products like Google Assistant, Photos, and Cloud AI services. Their responsibilities include data analysis, model building, testing, and deployment of AI models in production environments. These engineers often collaborate with researchers, data scientists, and product teams to solve complex problems using the latest advancements in AI and machine learning.

What are some common challenges faced by Google AI Engineers when deploying machine learning models to production?

Google AI Engineers often encounter challenges such as ensuring models are scalable and efficient enough to handle large-scale data, maintaining model performance over time, and addressing issues related to fairness and bias. Collaborating with cross-functional teams, such as product managers and software engineers, is crucial for aligning technical solutions with product goals. Additionally, AI Engineers must keep up with evolving frameworks and best practices to optimize deployment pipelines and monitor models post-launch for potential drift or degradation.

What is the difference between Google Ai Engineer vs Machine Learning Engineer?

AspectGoogle Ai EngineerMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related fields; experience with AI frameworksBachelor's or higher in CS, Data Science, or related fields; strong programming skills
Work EnvironmentTech companies, research labs, AI-focused teamsTech firms, startups, data-driven organizations
Industry UsagePrimarily in AI product development at Google and similar companiesAcross various industries implementing ML solutions
Common Search/ComparisonYesYes

The Google AI Engineer and Machine Learning Engineer roles share many credentials and work environments, but AI Engineers focus more on developing advanced AI models and research, while ML Engineers often implement and optimize machine learning algorithms for practical applications across industries.

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

To thrive as a Google AI Engineer, you need a strong background in computer science, mathematics, and machine learning, typically supported by a relevant degree and experience in algorithm development. Familiarity with TensorFlow, Python, cloud computing platforms, and often certifications in AI or data science are essential for daily tasks. Problem-solving abilities, creativity, and effective collaboration are standout soft skills in this role. These skills are vital for developing innovative AI solutions that align with Google’s standards of performance, scalability, and impact.
More about Google Ai Engineer jobs
What cities are hiring for Google Ai Engineer jobs? Cities with the most Google Ai Engineer job openings:
What states have the most Google Ai Engineer jobs? States with the most job openings for Google Ai Engineer jobs include:
What job categories do people searching Google Ai Engineer jobs look for? The top searched job categories for Google Ai Engineer jobs are:
Google Ai Engineer jobs near you
Infographic showing various Google Ai Engineer job openings in the United States as of July 2026, with employment types broken down into 73% Full Time, 24% Part Time, and 3% Contract. Highlights an 65% Physical, 3% Hybrid, and 32% Remote job distribution, with an average salary of $101,752 per year, or $48.9 per hour.

AI Engineer - Google AI & Generative Intelligence - Full Time Role

Saransh Inc

Paramus, NJ • On-site

$98K - $135K/yr

Full-time

Posted 17 days ago

Job description

Role: AI Engineer – Google AI & Generative Intelligence
Location: Paramus, NJ (All the 5 days a week onsite is required)
Job Type: Full Time
 
Experience Required: 10–15 Years in Software Engineering | 3+ Years in Artificial Generative Intelligence
 
Role Overview:
  • We are seeking a highly experienced Senior AI Engineer with deep expertise in Google AI technologies and Generative AI.
  • The ideal candidate brings 10–15 years of broad software engineering experience, with the last 2+ years focused exclusively on Artificial Generative Intelligence, including designing, building, deploying, and monitoring production-grade AI systems.
  • This role demands mastery of the Google ecosystem — including Google Workspace, Google Agent Development Kit (ADK), and Vertex AI — alongside a strong command of modern LLM/SLM frameworks, cloud-native infrastructure, and MLOps best practices.
Key Responsibilities:
1. AI Engineering
Design, develop, and deploy Agents leveraging commercial LLMs such as Gemini (Google), GPT (OpenAI), and Claude Sonnet (Anthropic) for high-performance, large-context, and multimodal tasks.
2. Google AI & Workspace Integration
Lead the design and implementation of AI-powered solutions deeply integrated with Google Workspace (Docs, Sheets, Drive, Gmail, Meet), Big Query and Lakehouse.
Architect and build intelligent agents and workflows using Google Agent Development Kit (ADK).
Leverage Google AI Studio as the primary IDE, VSCode for AI application development and prototyping.
Utilize Google Cloud Platform (GCP) services including:
Vertex AI for ML model training, tuning, and deployment
Vertex AI Vector DBs for semantic search and retrieval
3. Design & Planning
Lead requirements gathering using Confluence for documentation and team collaboration.
Create detailed system architecture diagrams and AI workflows using Lucidchart.
Manage project delivery and sprint planning using Jira.
4. Development Frameworks & Tools
Orchestrate LLM/SLM applications using LangChain, LlamaIndex, and LangGraph.
Build multi-agent systems with Semantic Kernel, and LangGraph.
Manage and optimize prompts using LangSmith and PromptLayer.
Manage code and data versioning with Git.
5. Vector Databases & Semantic Search
Implement semantic search and Retrieval-Augmented Generation (RAG) pipelines using Vertex AI Vector DBs and ChromaDB.
Design and optimize end-to-end RAG architectures for enterprise-grade knowledge retrieval.
6. Backend Development
Develop robust RESTful APIs using FastAPI (Python) or Express.js (Node.js).
Manage and secure APIs using Mulesoft, Apigee.
7. Frontend Development
Drupal Content Management System (PHP Backend + JS Frontend) - Drupal 10.4, PHP 8.1
Build modern user interfaces using React or Angular.
Utilize Material-UI for consistent, accessible, and modern UI components.
OAuth2 authentication.
8. Development Tools & Code Quality
Write and debug code in VS Code with Python and GitHub Copilot extensions.
Manage source code with GitHub or GitLab.
Enforce code quality and standards using SonarQube, ESLint, and Pylint.
9. Testing & Quality Assurance
Conduct LLM-specific testing using RAGAS and DeepEval for LLM/RAG pipeline evaluation.
Use LangSmith Evaluators for prompt testing and hallucination detection.
Write and execute unit tests using pytest.
Ensure output quality and reliability using LangChain Evaluators and custom metrics.
10. Deployment & Infrastructure.
 Support on-premise, cloud (GCP/Vertex AI), and hybrid infrastructure deployments including edge devices for local inference.
 
Required Qualifications:
  • 10–15 years of overall software engineering experience.
  • 3+ years of hands-on experience in Artificial Generative Intelligence, including LLMs, SLMs, RAG, and multi-agent systems.
  • Deep expertise in Google AI ecosystem: Gemini, Vertex AI, Google ADK, Google AI Studio, and Google Workspace integrations.
  • Proficiency in Python (primary) and familiarity with Node.js.
  • Strong background in cloud-native development on GCP.
  • Experience with multi-agent AI architectures using Semantic Kernel, or LangGraph.