ZipRecruiter

Log In

2

Full Time Google Ai Jobs (NOW HIRING)

Noblesoft Technologies

AI Architect

Paramus, NJ · On-site

Paramus, NJ / Hybrid Full- Time Role Role Overview: We are seeking a highly accomplished AI Architect with deep expertise in Google AI technologies and Generative AI to lead the design and ...

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 ... Benefits Our comprehensive benefits package for full-time salaried employees is effective ...

PGTEK

Lead Cloud AI Engineer - Travel role

Tampa, FL · 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 ... Benefits Our comprehensive benefits package for full-time salaried employees is effective ...

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 ... Benefits Our comprehensive benefits package for full-time salaried employees is effective ...

PGTEK

Lead Cloud AI Engineer - Travel role

Tampa, FL

$120K - $150K/yr

As we expand our Google Cloud and AI practice, we're seeking a Lead Cloud AI Engineer to serve as ... Benefits Our comprehensive benefits package for full-time salaried employees is effective ...

next page

Showing results 1-20

All Jobsfull time JobsTechnology JobsFull Time Google Ai Jobs

Full Time Google Ai information

What cities are hiring for Full Time Google Ai jobs?

Cities with the most Full Time Google Ai job openings:

What are the most commonly searched types of Google Ai jobs?

The most popular types of Google Ai jobs are:

What states have the most Full Time Google Ai jobs?

States with the most job openings for Full Time Google Ai jobs include:

What job categories do people searching Full Time Google Ai jobs look for?

The top searched job categories for Full Time Google Ai jobs are:

Full Time Google Ai jobs near you
Infographic showing various Full Time Google 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.

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

Paramus, NJ • On-site

Saransh Inc
IT Services • 51 - 200 employees
Learn more about Saransh Incexternal

$98K - $135K/yr

Full-time

Re-posted 24 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.