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Chatbot Manager Jobs in Florida (NOW HIRING)

EnerSys

Senior Finance AI & Automation Developer

Lakeland, FL · On-site +1

$95K - $119K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

AI Agent & Chatbot Projects * AI Workflow Projects * Predictive Modeling Projects * Educate Finance Team about AI Applications & Tools * Project Documentation and Change Management * Finance ...

Watershed Ventures

Principal Engineer

Orlando, FL · On-site

$120 - $160/hr

Not a chatbot. Real, deep infrastructure that changes how care gets delivered. We're Series A ... Overseeing the architecture of AI‑powered features (voice agents, clinical workflows), managing ...

Foundationhealth

Principal Engineer

Orlando, FL · On-site

$130 - $170/hr

  • Medical

  • Dental

  • Vision

  • Life

  • PTO

Not a chatbot. Real, deep infrastructure that changes how care gets delivered. We're Series A ... Overseeing the architecture of AI-powered features (voice agents, clinical workflows), managing ...

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All JobsChatbot JobsChatbot Manager JobsChatbot Manager Jobs in Florida

Chatbot Manager information

What is a chatbot manager?

A Chatbot Manager is a professional responsible for overseeing the development, deployment, and optimization of chatbots for organizations. They coordinate between technical teams, content creators, and stakeholders to ensure chatbots provide effective customer service, support, or engagement. Their duties include analyzing chatbot performance, managing updates, and implementing improvements based on user feedback and analytics. Chatbot Managers also stay updated with the latest AI and conversational technologies to enhance user experience.

What are the key skills and qualifications needed to thrive as a chatbot manager?

To thrive as a Chatbot Manager, you need expertise in conversational design, data analysis, and a solid understanding of AI and natural language processing, often backed by a degree in computer science or a related field. Familiarity with chatbot platforms (like Dialogflow or Microsoft Bot Framework), analytics tools, and experience with APIs or scripting languages is typically required. Strong communication, problem-solving, and project management skills help you collaborate across teams and optimize user experiences. These skills are crucial for developing effective, user-friendly chatbots that drive customer engagement and achieve business objectives.

What are some common challenges faced by a chatbot manager when optimizing bot performance, and how are they typically addressed?

A Chatbot Manager often encounters challenges such as ensuring the chatbot accurately understands user intent, maintaining up-to-date responses, and handling complex or ambiguous queries. To address these, managers regularly analyze chat logs for patterns, work closely with data analysts and conversational designers to refine scripts, and implement continuous training for the chatbot using real user data. Collaborating with customer support and product teams helps ensure the bot remains aligned with evolving business needs and delivers consistent, high-quality user experiences.

What is the difference between Chatbot Manager vs Chatbot Developer?

AspectChatbot ManagerChatbot Developer
Primary RoleOversees chatbot projects, manages teams, and ensures chatbot performance aligns with business goals.Designs, codes, and implements chatbot functionalities and features.
Required SkillsProject management, communication, understanding of AI and NLP concepts.Programming languages (Python, JavaScript), AI/NLP development skills.
Work EnvironmentTypically in managerial or coordination roles within tech or customer service industries.Hands-on coding and development in software or AI teams.
Common CertificationsProject management certifications, AI/NLP courses.Programming certifications, AI/NLP training.

While a Chatbot Manager oversees the overall chatbot strategy and team, a Chatbot Developer focuses on building and coding the chatbot functionalities. Both roles often collaborate but differ in their core responsibilities and skill sets.

What are the most commonly searched types of Chatbot jobs in Florida?

The most popular types of Chatbot jobs in Florida are:

What are popular job titles related to Chatbot Manager jobs in Florida?

For Chatbot Manager jobs in Florida, the most frequently searched job titles are:

What job categories do people searching Chatbot Manager jobs in Florida look for?

The top searched job categories for Chatbot Manager jobs in Florida are:

What cities in Florida are hiring for Chatbot Manager jobs?

Cities in Florida with the most Chatbot Manager job openings:

Chatbot Manager jobs near you
Infographic showing various Chatbot Manager job openings in Florida as of August 2026, with employment types broken down into 87% Full Time, 12% Part Time, and 1% Contract. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution.

AI & GEO Solutions Engineer

SNI Technology

Winter Garden, FL • On-site

$130K - $140K/yr

Other

Re-posted 6 days ago

Job description

AI Solutions Engineer / AI Applications Developer
Location: Onsite in Orlando
Pay Range: $130,000-$140,000
Please Note: NO C2C, Agency referrals or sponsorship available
Position Overview:
This role is responsible for designing, developing, and supporting AI-enabled capabilities across web platforms, e-commerce systems, and enterprise applications. The position partners closely with cross-functional teams to enhance AI-driven discoverability, user engagement, and business workflows while ensuring responsible and scalable AI implementation.
Key Responsibilities
  • Analyze, design, develop, test, deploy, and document AI-powered enhancements across websites, e-commerce platforms, intranet applications, APIs, and enterprise systems
  • Support Generative Engine Optimization (GEO) initiatives to improve AI model discoverability, AI-generated brand visibility, and semantic search performance
  • Collaborate with Web, Marketing, Product, Content, SEO/GEO, and Technology teams to optimize structured content, metadata, schema markup, and AI-readable content frameworks
  • Evaluate, configure, integrate, and maintain third-party AI platforms, LLM-based systems, APIs, chatbot tools, knowledge bases, vector search solutions, and workflow automation technologies
  • Design and support AI-driven engagement solutions such as intelligent search, AI assistants, recommendation engines, conversational interfaces, and knowledge retrieval systems
  • Implement and support structured data frameworks including schema standards, embeddings, retrieval-augmented generation (RAG), vector databases, and semantic search architectures
  • Translate business objectives into technical requirements, implementation plans, testing strategies, documentation, and development-ready tasks
  • Act as a liaison between business stakeholders and technical teams for AI initiatives, including requirements gathering, workflow design, testing coordination, and deployment
  • Monitor competitive AI presence, AI-search trends, and evolving AI discovery and commerce strategies
  • Assess AI tools for privacy, security, performance, hallucination risks, data governance, and operational considerations prior to implementation
  • Support enterprise AI governance initiatives, including data stewardship, approval workflows, and responsible AI standards
  • Research emerging AI technologies, platforms, and industry trends relevant to digital commerce, customer engagement, and enterprise operations
  • Drive measurable improvements in AI visibility, semantic discoverability, workflow automation, and AI-assisted user experience

Required Skills & Competencies
  • Strong analytical, problem-solving, and organizational skills
  • Excellent communication skills with the ability to translate technical concepts into business language
  • Ability to work both independently and collaboratively in cross-functional environments
  • Strong project management and prioritization capabilities in fast-paced settings

AI & Technical Knowledge
  • Solid understanding of:
  • Large Language Models (LLMs)
  • Prompt engineering
  • Retrieval-Augmented Generation (RAG)
  • Embeddings and vector search
  • Semantic search and AI orchestration workflows
  • AI testing and evaluation frameworks
  • Knowledge of:
  • Generative Engine Optimization (GEO) and technical SEO
  • Semantic web architecture and structured content optimization
  • AI governance, privacy, security, bias mitigation, and responsible AI practices

Technology Familiarity
Experience with or exposure to tools and platforms such as:
  • OpenAI, Anthropic, Google Gemini
  • AWS Bedrock, Azure AI, Vertex AI
  • LangChain, LlamaIndex
  • Vector databases (e.g., Pinecone, Weaviate)

Nice to have: Experience with enterprise ERP or commerce platforms and integrations
Minimum Qualifications
  • Bachelor's degree in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, or a related field
  • 5+ years of experience developing or supporting enterprise web applications, APIs, or business systems
  • 2+ years of hands-on experience working with AI tools, LLM systems, AI APIs, or automation platforms
  • 5+ years of experience integrating third-party systems using REST APIs, SDKs, and modern integration frameworks
  • Experience with modern web technologies such as JavaScript, TypeScript, HTML/CSS, front-end frameworks, and back-end development (e.g., Java, C#, .NET, Node.js)
  • Experience with relational databases, SQL, and enterprise data models

Preferred Experience
  • Hands-on experience with:
  • AI integrations and workflows
  • Semantic search and vector databases
  • Chatbots and conversational AI
  • Knowledge retrieval systems and AI orchestration pipelines
  • Familiarity with:
  • Structured data and schema markup
  • AI indexing, semantic architecture, and SEO/GEO concepts
  • Cloud deployment, monitoring, and enterprise application support tools (e.g., Git, Jira, Postman)

Additional Requirements
  • Proven ability to gather requirements, identify gaps, and translate business needs into actionable plans
  • Strong collaboration skills across technical teams, business stakeholders, and external partners
  • Awareness of AI privacy, compliance, security, and risk management considerations
  • Ability to stay current with rapidly evolving AI technologies and industry trends
  • Comfortable working in dynamic environments with shifting priorities and emerging technologies
#SNIT

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