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Generative Ai Chatbot Jobs (NOW HIRING)

SID Global Solutions

AI Lead Developer

Exton, PA

$57 - $74.50/hr

Key Responsibilities Design and develop enterprise-grade Agentic AI and Generative AI solutions ... What We're Looking For A senior AI engineering leader who can move beyond chatbot development and ...

Oraapps Inc

Senior Staff Software Engineer

Manhattan, NY · On-site

$135K - $178K/yr

AI Engineer, Machine Learning Engineer, Staff Software Engineer, Python, LLM, Generative AI, RAG, AI Agents, OpenAI, PyTorch, TensorFlow, Machine Learning, ML Pipeline, Recommendation Engine, Chatbot ...

National Debt Relief, LLC.

Engineer, Applied AI

$129K - $149K/yr

... Generative AI (GenAI) solutions. This is an exciting opportunity to build and deploy real-world ... Your work will span chatbot development, document processing, summarization, voice AI, and AI ...

BC Forward

Content Strategist III

Indianapolis, IN · On-site

$51 - $55/hr

... chatbot and Help Center content, and enable Generative AI-driven support experiences. Responsibilities: Conduct Root Cause Analyses on user support tickets to identify chatbot issues, including ...

Esri

Python generative AI, large language models, and agentic systems * Web AI chatbot interfaces * Web data visualization techniques combining AI results with 2D and 3D maps * GIS * REST Web services

Aquent

Content Strategist III

Austin, TX · On-site +1

$44 - $58/hr

Your work will be crucial in building content that fuels cutting-edge Generative AI experiences ... Thoroughly test and validate the support chatbot to verify issue resolution post-fix, debugging ...

SID Global Solutions

AI Lead Developer

Exton, PA · On-site

$57 - $74.50/hr

Design and develop enterprise-grade Agentic AI and Generative AIsolutions. * Build multi-agent ... What We're Looking For A senior AI engineering leader who can move beyond chatbot development and ...

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Generative Ai Chatbot information

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$54K

$103.1K

$190.5K

How much do generative ai chatbot jobs pay per year?

As of Jun 27, 2026, the average yearly pay for generative ai chatbot in the United States is $103,131.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,500.00 and $120,000.00 per year, depending on experience, location, and employer.

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 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 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.
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Generative Ai Chatbot jobs near you
AI Lead Developer

AI Lead Developer

SID Global Solutions

Exton, PA

$57 - $74.50/hr

Full-time

Posted 22 days ago

Job description

AI Lead Developer - Agentic AI & GenAI Solutions Location: Exton, PA Onsite Employment Type: Full-Time We are seeking a hands-on AI Lead Developer to architect, build, and deploy enterprise-scale Agentic AI, Generative AI, and Multi-Agent Solutions. This role requires strong expertise in AI architecture, LLM-powered applications, cloud-native deployments, and scalable AI platforms. The ideal candidate will lead the development of intelligent AI systems while mentoring engineering teams and driving AI innovation across the organization.

Career Growth Opportunity This role is designed to evolve into a leadership position with the opportunity to grow into a Global AI Practice Head, leading AI strategy, delivery, innovation, and capability development across global teams. Key Responsibilities Design and develop enterprise-grade Agentic AI and Generative AI solutions. Build multi-agent systems using LangGraph, AutoGen, ADK, MCP, and related frameworks.

Develop RAG-based applications leveraging vector databases and enterprise knowledge sources. Build scalable APIs and AI microservices using Python, FastAPI, and cloud-native architectures. Deploy AI solutions on AWS, Azure, or GCP using Docker, Kubernetes, and CI/CD pipelines.

Implement AI security, governance, observability, and guardrails. Collaborate with business, product, and engineering teams to deliver AI-driven solutions. Conduct code reviews, mentor engineers, and contribute to AI architecture and roadmap planning.

Required Skills 10+ years of software engineering experience with 4+ years in AI/GenAI solutions. Strong Python development experience with FastAPI or Flask. Hands-on experience with: LangChain LangGraph AutoGen ADK MCP (Model Context Protocol) Multi-Agent Architectures Experience building RAG pipelines, embeddings, prompt engineering, and vector search solutions.

Experience with vector databases such as Pinecone, Weaviate, FAISS, Chroma, or Azure AI Search. Strong knowledge of REST APIs, microservices, distributed systems, and cloud platforms (AWS/Azure/GCP). Experience with Docker, Kubernetes, Redis, Kafka, and AI application deployment.

Strong understanding of AI security, memory management, scalability, and production AI systems. Preferred Skills Experience with OpenAI, Azure OpenAI, Claude, Gemini, and Hugging Face models. Knowledge of MLOps, AI evaluation frameworks, and AI governance.

Experience with Spark, Kafka, and large-scale AI platforms. Prior experience leading AI initiatives and mentoring engineering teams. What We're Looking For A senior AI engineering leader who can move beyond chatbot development and build production-grade, enterprise-scale Agentic AI platforms, while helping shape the future AI strategy and practice of the organization.

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