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Generative Ai Chatbot Jobs in Edison, NJ (NOW HIRING)

VeridianTech

AI Architect

Jersey City, NJ · On-site

$65.75 - $86.75/hr

Key Responsibilities Lead the strategy, architecture, and technical design of enterprise AI, Generative AI, and Agentic AI solutions. Architect sophisticated conversational AI/chatbot platforms ...

Ansell

Senior AI Engineer

Iselin, NJ · Hybrid

$106K - $145K/yr

The Senior AI Engineer is a technical leader with deep expertise in AI/ML, Generative AI, Large ... Integrate Large Language Models into chatbot workflows for summarization, classification, and ...

Bank of America

Data Scientist II

New York, NY · On-site

A Generative AI powered "chatbot-like" search platform that enables sales and product teams to quickly find high quality answers to product, servicing, and client related questions * A comprehensive ...

All JobsGenerative Ai Chatbot JobsGenerative Ai Chatbot Jobs in Edison, NJ

Generative Ai Chatbot information

See Edison, NJ salary details

$55.9K

$106.8K

$197.2K

How much do generative ai chatbot jobs pay per year?

As of Sep 7, 2026, the average yearly pay for generative ai chatbot in Edison, NJ is $106,767.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,300.00 and $124,200.00 per year, depending on experience, location, and employer.

What is a generative AI chatbot?

A Generative AI Chatbot is an artificial intelligence system designed to engage in human-like conversations by generating responses to user inputs in real time. Unlike traditional rule-based chatbots that rely on predefined scripts, generative AI chatbots use advanced machine learning models—often based on large language models—to understand context and produce original, relevant responses. These chatbots can be used in customer service, education, entertainment, and more, offering personalized and dynamic interactions. They continue to improve as they process more data and user interactions.

What are some common challenges faced by professionals working on generative AI chatbot development, and how can they be addressed?

Professionals developing generative AI chatbots often encounter challenges such as managing ambiguous user inputs, ensuring conversational relevance, and maintaining ethical standards like avoiding biased or inappropriate responses. Collaboration with interdisciplinary teams—including data scientists, linguists, and UX designers—is vital to continuously improve the chatbot's performance. Regular testing, user feedback, and fine-tuning of language models are essential practices to address these challenges and enhance the chatbot's ability to handle diverse real-world conversations.

What are the key skills and qualifications needed to thrive as a generative AI chatbot developer, and why are they important?

To thrive as a Generative AI Chatbot Developer, you need strong programming expertise (especially in Python), a solid understanding of machine learning and natural language processing (NLP), and typically a degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with APIs, and knowledge of cloud platforms such as AWS or Azure are commonly required, along with relevant AI or ML certifications. Creativity, problem-solving, and effective communication are vital soft skills for designing engaging, user-friendly conversational experiences and collaborating with cross-functional teams. These skills are crucial for building reliable, scalable, and innovative AI chatbots that meet user needs and business objectives.

What is the difference between Generative Ai Chatbot vs Data Scientist?

AspectGenerative Ai ChatbotData Scientist
Required CredentialsBasic programming, AI/ML knowledgeDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, customer service platformsResearch labs, corporate analytics teams
Industry UsageAutomated customer interactions, content generationData analysis, predictive modeling, insights
Search & Comparison IntentUnderstanding AI chatbot capabilitiesData analysis skills and roles

Generative Ai Chatbots focus on creating conversational AI for customer engagement, requiring programming and AI knowledge. Data Scientists analyze data to generate insights, often with advanced degrees. While both work in tech environments, their roles differ in purpose and skill set.

What are popular job titles related to Generative Ai Chatbot jobs in Edison, NJ?

For Generative Ai Chatbot jobs in Edison, NJ, the most frequently searched job titles are:

What job categories do people searching Generative Ai Chatbot jobs in Edison, NJ look for?

The top searched job categories for Generative Ai Chatbot jobs in Edison, NJ are:

What cities near Edison, NJ are hiring for Generative Ai Chatbot jobs?

Cities near Edison, NJ with the most Generative Ai Chatbot job openings:

Generative Ai Chatbot jobs near you

AI Architect

VeridianTech

Jersey City, NJ • On-site

$65.75 - $86.75/hr

Other

Posted 4 days ago

Job description

AI Architect
Core Technical Skills

Must Have:
Google Cloud Platform Generative AI LLMs Agentic AI Multi-Agent / A2A Systems Complex Chatbots / Conversational AI RAG Knowledge Graphs Machine Learning MCP Python Enterprise AI Architecture Document AI / Document Processing

We are seeking an experienced AI Solutions Architect to lead the strategy, architecture, and design of complex enterprise AI and Generative AI solutions. This individual will partner closely with business stakeholders, engineering teams, data teams, and leadership to translate business requirements into scalable AI architectures and drive technical conversations from concept through implementation.

The ideal candidate will have deep experience designing high-complexity conversational AI and chatbot solutions, including agentic AI, multi-agent architectures, and agent-to-agent (A2A) interactions. This role requires a strong combination of AI architecture, machine learning, cloud, data, and hands-on technical expertise.

Key Responsibilities

Lead the strategy, architecture, and technical design of enterprise AI, Generative AI, and Agentic AI solutions.

Architect sophisticated conversational AI/chatbot platforms capable of supporting complex workflows, reasoning, orchestration, and enterprise integrations.

Design agentic and multi-agent AI architectures, including agent-to-agent transactions, communication, orchestration, tool usage, and workflow execution.

Design and implement Retrieval-Augmented Generation (RAG) architectures leveraging enterprise structured and unstructured data.

Architect solutions utilizing knowledge graphs to improve contextual understanding, reasoning, relationships, and information retrieval.

Develop and guide machine learning and Generative AI solutions across enterprise use cases.

Design AI architectures leveraging Model Context Protocol (MCP) to securely connect AI agents and models with enterprise tools, systems, APIs, and data sources.

Architect and deploy AI/ML solutions within Google Cloud Platform (Google Cloud Platform), leveraging appropriate cloud-native AI, data, compute, and integration services.

Lead architecture discussions and technical strategy sessions with senior business and technology stakeholders.

Translate complex business requirements and technical documentation into clear AI solution designs, architecture patterns, roadmaps, and implementation strategies.

Evaluate AI technologies, models, frameworks, and architectural approaches and provide recommendations based on business and technical requirements.

Establish best practices around AI scalability, security, governance, performance, reliability, and responsible AI.

Provide technical leadership and architectural guidance to engineering, data science, machine learning, and platform teams.

Develop prototypes and reference implementations using Python to validate architectural concepts and AI capabilities.

Required Qualifications

Extensive experience as an AI Solutions Architect, AI Architect, ML Architect, or similar senior technical architecture role.

Strong experience architecting complex enterprise chatbot and conversational AI solutions.

Deep understanding of Agentic AI and multi-agent systems, including agent-to-agent (A2A) communication, orchestration, reasoning, tool calling, and autonomous workflows.

Strong hands-on experience with Generative AI and Large Language Models (LLMs).

Strong experience designing and implementing Retrieval-Augmented Generation (RAG) solutions.

Experience with knowledge graphs, semantic relationships, graph-based retrieval, and/or knowledge-driven AI architectures.

Strong foundation in machine learning concepts, architectures, and production ML solutions.

Experience with Model Context Protocol (MCP) and integrating AI applications/agents with enterprise systems, APIs, tools, and data.

Deep experience with Google Cloud Platform (Google Cloud Platform) and building scalable AI/ML solutions in the Google Cloud Platform ecosystem.

Strong Python development experience for AI/ML applications, integrations, prototyping, and solution development.

Experience working with structured and unstructured enterprise data, including document ingestion, extraction, translation, summarization, and intelligent document processing.

Strong understanding of APIs, microservices, cloud architecture, data integration, security, and enterprise application architecture.

Ability to communicate complex AI concepts to both technical and non-technical stakeholders.

Demonstrated ability to drive AI strategy, influence architectural decisions, and lead technical conversations across multiple teams.

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