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Assistant Google Ai Jobs (NOW HIRING)

Qaurs Techno Systems LLC

AI Engineer

Charlotte, NC · On-site

If you have a strong foundation in Java and Python, coupled with hands-on experience using Google ... Leverage AI and LLMs to build systems that assist in, or fully automate, code generation, testing ...

Instant Serve LLC

AI Data Architect /REMOTE

Denver, CO · Remote

$75 - $80/hr

Expertise in AI/ML tools and models (e.g., Google Vertex, AWS Kendra, Snowflake Cortex, AWS ... This is a dedicated line designed exclusively to assist job seekers whose disability prevents them ...

Paramount

VP, SEO & AI Discovery

Manhattan, NY · On-site

This role owns how our content gets found, cited, and surfaced - across Google, emerging answer engines (ChatGPT, Perplexity, Claude, Gemini, Microsoft Copilot), AI Overviews, voice assistants, and ...

Paramount

VP, SEO & AI Discovery

Manhattan, NY · On-site

This role owns how our content gets found, cited, and surfaced - across Google, emerging answer engines (ChatGPT, Perplexity, Claude, Gemini, Microsoft Copilot), AI Overviews, voice assistants, and ...

STI

AI Data Architect

$65.25 - $84/hr

Provide guidance and support on technical and ethical considerations and assist with strengthening ... Google Vertex, AWS Kendra, Snowflake Cortex, AWS SageMaker, Google AI Studio), cloud computing (i.e ...

Peec AI

AI Search Strategist

New York, NY · On-site

$100K - $150K/yr

... Google's AI Overviews instead of traditional search, and most brands have no idea where they show ... AI assistants, and emerging generative surfaces. You'll combine deep SEO expertise with a ...

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Assistant Google Ai information

What does an Assistant Google AI do?

Assistant Google AI roles involve working on the development, improvement, and deployment of artificial intelligence technologies that power Google Assistant and related products. Professionals in these roles may focus on natural language processing, voice recognition, machine learning, and user experience design to make interactions with Google Assistant more helpful and intuitive. Their responsibilities often include researching new AI methods, training models, testing features, and addressing user feedback to enhance product performance. These roles are crucial for creating smarter, more responsive virtual assistants that can understand and assist users in everyday tasks.

What are the typical collaboration opportunities for an Assistant Google AI within cross-functional teams?

As an Assistant Google AI, you will frequently collaborate with product managers, software engineers, UX designers, and data scientists to enhance AI-driven features and user experiences. This role often involves participating in brainstorming sessions, providing feedback on product development, and integrating AI solutions that align with business objectives. Effective communication and teamwork are essential, as you'll be expected to translate complex AI concepts into actionable insights for non-technical stakeholders. This collaborative environment not only broadens your skill set but also provides ample opportunities for professional growth and learning from experts across different domains.

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

To thrive as an Assistant Google AI, you need a strong background in computer science, machine learning, and natural language processing, usually supported by a relevant degree and experience in AI research or development. Familiarity with AI frameworks (such as TensorFlow), cloud platforms, and programming languages like Python is essential, along with certifications in machine learning or data science. Strong analytical thinking, problem-solving abilities, and effective communication set top performers apart in this field. These skills and qualities are crucial for building, optimizing, and supporting advanced AI solutions that meet user needs and business goals.

What is the difference between Assistant Google Ai vs Chatbot Developer?

AspectAssistant Google AiChatbot Developer
Required CredentialsTechnical certifications, AI/ML knowledgeProgramming skills, AI/ML understanding
Work EnvironmentTech companies, AI development teamsSoftware companies, customer service platforms
Employer & Industry UsageGoogle, AI and tech industriesVarious industries including retail, finance, and customer support
Common Search & Comparison IntentUnderstanding AI assistant capabilitiesBuilding or improving chatbots

Assistant Google Ai focuses on developing and managing AI-powered virtual assistants like Google Assistant, emphasizing natural language processing and user interaction. Chatbot Developers design and build chatbots for various platforms, often requiring programming and AI skills. While both roles involve AI and machine learning, Assistant Google Ai professionals typically work within larger tech ecosystems, whereas Chatbot Developers may work across diverse industries to create customer service solutions.

More about Assistant Google Ai jobs

What cities are hiring for Assistant Google Ai jobs?

Cities with the most Assistant 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 Assistant Google Ai jobs?

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

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

The top searched job categories for Assistant Google Ai jobs are:

Assistant Google Ai jobs near you
Infographic showing various Assistant Google Ai job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 21% Part Time, 1% Temporary, and 2% Contract. Highlights an 98% Physical, 1% Hybrid, and 1% Remote job distribution.

AI Engineer

Qaurs Techno Systems LLC

Charlotte, NC • On-site

Full-time

Re-posted 7 days ago

Job description


Experience: 5 + Years
AI Engineer Job Summary:
We are seeking an innovative and highly skilled AI Engineer to join our dynamic team. The ideal candidate will bridge the gap between traditional software engineering and cutting-edge artificial intelligence. You will be instrumental in designing, building, and deploying advanced AI agents, working closely with Large Language Models (LLMs), and driving automated code generation initiatives. If you have a strong foundation in Java and Python, coupled with hands-on experience using Google's AI tools, we want you to help us build the next generation of intelligent applications.
Key Responsibilities:
* AI Agent Development: Design, build, and deploy autonomous AI agents capable of reasoning, planning, and executing complex workflows.
* LLM Integration: Integrate cutting-edge Large Language Models (LLMs) into our core products and services to enhance functionality and user experience.
* Model Context Protocol (MCP) Implementation: Utilize the Model Context Protocol (MCP) to securely connect our AI models to various data sources, tools, and development environments.
* Automated Code Generation: Leverage AI and LLMs to build systems that assist in, or fully automate, code generation, testing, and optimization processes.
* System Engineering: Write clean, scalable, and maintainable code in both Java and Python to support AI backend infrastructure.
* Google Ecosystem Integration: 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 product managers, data scientists, and frontend engineers to translate business requirements into technical AI solutions. Must-Have Qualifications:
* Programming Languages: Strong proficiency in both Java and Python, with a proven track record of building production-grade software.
* Google AI Tools: Hands-on experience with Google ADK (or equivalent Google Cloud AI/Vertex AI tools).
* LLM Expertise: Deep comfort level and practical experience working with Large Language Models (prompt engineering, fine-tuning, RAG architectures).
* Agentic Workflows: Demonstrable experience in building and orchestrating AI Agents (using frameworks like LangChain, LangGraph, or custom implementations).
* MCP Knowledge: Familiarity and practical experience with the Model Context Protocol (MCP) for standardizing AI interactions with external tools.
* Code Generation: Experience in leveraging AI tools or building pipelines specifically for code generation and software automation. Good-to-Have (Optional but highly valued):
* Experience with modern robust backend frameworks (e.g., Spring Boot for Java, FastAPI for Python).
* Familiarity with containerization and orchestration (Docker, Kubernetes).
* Experience with vector databases (e.g., Pinecone, Weaviate, Milvus).