Conversational AI Developer at Bill Alexander Ford Lincoln
Boston, Massachusetts, United States -
Full Time


Start Date

Immediate

Expiry Date

17 May, 26

Salary

150000.0

Posted On

16 Feb, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Conversational AI, Chatbots, Voice Assistants, NLU, Dialogue Management, Python, Java, Node.js, TensorFlow, PyTorch, Scikit-learn, REST APIs, Webhooks, Cloud Deployment, NLP, Machine Learning

Industry

Description
The Conversational AI Developer designs, develops, and deploys AI-driven conversational solutions, including chat bots, voice assistants, and intelligent virtual agents. This role involves building natural language understanding (NLU), dialogue management, and integration with business systems to deliver seamless, context-aware user experiences. The Conversational AI Developer collaborates closely with product managers, UX designers, data scientists, and software engineers to create scalable AI-driven applications. This position is strictly limited to candidates who currently reside in the United States and are legally authorized to work in the U.S. Applications from individuals residing outside the United States will be rejected. Key Responsibilities Design, develop, and deploy conversational AI solutions, including chatbots and voice assistants Implement NLU, intent recognition, entity extraction, and dialogue management models Integrate conversational AI solutions with internal systems, APIs, and third-party platforms Optimize AI models for accuracy, response time, and contextual understanding Conduct testing, debugging, and performance monitoring of AI systems Collaborate with UX designers to ensure intuitive, human-centered conversational experiences Maintain and update AI training data, model versions, and system documentation Stay current with advancements in NLP, machine learning, and conversational AI technologies Provide technical guidance and support to cross-functional teams on AI implementation Required Qualifications Bachelors degree in Computer Science, Artificial Intelligence, Data Science, or a related field 3–5 years of experience in AI/ML development, NLP, or software engineering Proficiency with conversational AI platforms such as Dialogflow, Rasa, Microsoft Bot Framework, or Amazon Lex Strong programming skills in Python, Java, or Node.js Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn) Solid understanding of NLU, NLP, dialogue management, and intent classification Familiarity with REST APIs, webhooks, and cloud deployment Strong problem-solving, analytical, and communication skills Ability to work independently and effectively in a remote environment Preferred Qualifications Masters degree in AI, Machine Learning, or NLP Experience with voice-based AI and speech recognition technologies Knowledge of large language models (LLMs) and generative AI integration Familiarity with version control systems (Git) and CI/CD pipelines Prior experience developing enterprise-scale conversational AI applications Compensation Annual Salary Range: $110,000 – $150,000 USD, based on experience and expertise Performance-Based Bonus: Eligible, tied to project success and AI solution impact Benefits Comprehensive medical, dental, and vision insurance 401(k) retirement plan with employer matching Paid time off, paid holidays, and sick leave Life, short-term, and long-term disability insurance Flexible remote work arrangement Professional development, AI certification, and training reimbursement Employee wellness and assistance programs Work Authorization & Residency Requirement Must be legally authorized to work in the United States Must currently reside within the United States Applications from candidates outside the U.S. will not be considered
Responsibilities
The developer will design, develop, and deploy AI-driven conversational solutions such as chatbots and voice assistants, focusing on implementing NLU, intent recognition, and dialogue management models. Key tasks also involve integrating these solutions with business systems and optimizing AI models for performance and context awareness.
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