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$24K

$104.9K

$189K

How much do entry level chatbot train ai jobs pay per year?

As of Jun 8, 2026, the average yearly pay for entry level chatbot train ai in the United States is $104,863.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $120,000.00 per year, depending on experience, location, and employer.

What are some typical daily tasks for an Entry Level Chatbot Train AI position?

As an Entry Level Chatbot Train AI, your daily tasks usually involve reviewing and labeling chat conversations, identifying patterns in user queries, and providing feedback to improve the AI's language understanding. You may also help create or refine conversation scripts, test chatbot responses for accuracy, and document any issues you encounter. Collaboration with data scientists and engineers is common to ensure your insights help advance the chatbot's performance. This role is structured, detail-oriented, and offers the opportunity to learn about AI development from the ground up.

What are the key skills and qualifications needed to thrive as an Entry Level Chatbot AI Trainer, and why are they important?

To thrive as an Entry Level Chatbot AI Trainer, you typically need strong written communication skills, attention to detail, and a basic understanding of language processing, often supported by a bachelor's degree in a related field. Familiarity with annotation tools, content management systems, and sometimes basic programming or data labeling platforms is commonly required. Adaptability, problem-solving, and collaborative teamwork are valuable soft skills that help you excel in training AI models. These skills ensure that chatbot responses are accurate, contextually appropriate, and continuously improving for better user experiences.

What is the difference between Entry Level Chatbot Train Ai vs Data Annotator?

AspectEntry Level Chatbot Train AiData Annotator
Required CredentialsHigh school diploma or equivalent; some roles may prefer basic technical skillsHigh school diploma or equivalent; attention to detail essential
Work EnvironmentRemote or office-based; involves working with AI systems and softwarePrimarily remote or office-based; involves reviewing and labeling data
Industry UsageAI development, customer service automationData management, machine learning training
Common Search/ComparisonYesNo

Entry Level Chatbot Train Ai roles focus on training AI chatbots by providing conversational data, while Data Annotators label and categorize data for machine learning. Both roles require attention to detail and are essential in AI development, but they differ in specific tasks and focus areas.

What does an entry level chatbot AI trainer do?

An entry level chatbot AI trainer is responsible for teaching and improving artificial intelligence systems that power chatbots. Their daily tasks typically include reviewing chatbot conversations, labeling data, correcting errors, and providing feedback to help the AI understand language better. They work with teams of engineers and data scientists to ensure the chatbot can respond accurately and naturally to user questions. This role often requires attention to detail, good communication skills, and sometimes basic knowledge of programming or data annotation tools.
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Entry Level Chatbot Train Ai jobs near you
Infographic showing various Entry Level Chatbot Train Ai job openings in the United States as of May 2026, with employment types broken down into 81% Full Time, 15% Part Time, and 4% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $104,863 per year, or $50.4 per hour.
Chatbot, Conversational AI Engineer

Chatbot, Conversational AI Engineer

Euclid Innovations

Manhattan, NY

Other

Posted 5 days ago

Job description

Requisition ID P tracker ID HM Location Skill Level MOR4JP00023628 1387644 Cameron Tennock Bangalore Chatbot, Conversational AI Engineer Level 3
Summary:
The Application Infrastructure team is seeking a motivated Chatbot / Conversational AI Engineer to join the Chatbot team. A successful candidate will participate in all aspects of software development, working directly with chatbot experts, other developers and engineers within the team, and our internal clients who wish to adopt chatbot solutions as part of technology service delivery.
Job Responsibilities
- Act as a subject matter expert on the chatbot platform
- Develop integrations in Python and Groovy that enable virtual agents to interoperate with various systems
- Participate in every phase of the Software Development Lifecycle
- Create Generative Artificial Intelligence solutions and drive their adoption
- Understand, refine, and translate customer requirements into working software
- Create and enhance various utilities that support the chatbot platform
- Lead design and code reviews
- Work closely with a global team of engineers, SREs, and conversational AI experts
- Identify automation opportunities and lead the way in addressing them
- Train and refine intent detection models
- Continuous Improvement of production virtual agents
- Measure, demonstrate, and articulate the value of Artificial Intelligence solutions and automation#
- Support POCs and product demonstrations
QUALIFICATIONS
Primary Skill:
- Strong knowledge of software design and best practices
- Deep experience with Python coding and development
- Experience with JavaScript and Node.js and other software development frameworks and libraries
- Demonstrated knowledge and interest in Generative Artificial Intelligence / LLMs, model training, fine tuning and related APIs
- Familiarity with CI/CD practices and experience with GitHub and Jenkins
- Excellent written and verbal communication skills
- Deep experience with Agile development practices such as Scrum
- Strong background in Linux
- Solid understanding of NLP and Artificial Intelligence / Machine Learning concepts
You might also have:
- Experience designing, creating, and interfacing with Virtual Agents using Amelia, Kore.ai, Microsoft Copilot Studio or similar platform
- Sourcing and labeling training data for ML models
- Experience in generative Artificial Intelligence, and LLMs
- Familiarity with DevOps practices
- Knowledge of Docker, Kubernetes
- Experience with cloud platforms such as AWS and Azure
Team Profile:
Enterprise Technology & Services (ETS) delivers shared technology services for the Firm supporting all business applications and end users. ETS provides capabilities for all stages of the Firm's software development lifecycle, enabling productive coding, functional and integration testing, application releases, and ongoing monitoring and support for over 3,000 production applications.
ETS also delivers all workplace technologies (desktop, mobile, voice, video, productivity, intranet/internet) in integrated configurations that boost the personal productivity of our employees. Application and end user services are delivered on a scalable, secure, and reliable infrastructure composed of seamlessly integrated datacenter, network, compute, cloud, storage, and database services.
Within ETS, the Chatbot Team in Application Infrastructure provides a scalable Natural Language Understanding platform for designing and building virtual agent solutions that can be adapted to a variety of technology services.

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