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Chatbot Manager Jobs in Austin, TX (NOW HIRING)

PayIt is seeking a Technical Solutions Delivery Manager. You will own the path from client need to ... Ability to design AI-enabled workflows, not just prompt a chatbot: you have built reusable prompts ...

Enterprise Architect

Austin, TX · On-site +1

$130K - $150K/yr

... Chatbot, Unicom System Architect, Visio, SV-02, ServiceNow, ITIL, MuleSoft, Oracle Service Bus ... Position Overview Fathom Management is seeking an experienced Enterprise Architect with recent ...

New

Manage and maintain server platforms in the lab environment. * Build, configure, and validate DDR ... Leverage AI chatbot tools for log analysis, scripting assistance, and documentation. * Document ...

AWS Sr. Developer Node.js/TypeScript

Austin, TX · Remote

$52.50 - $67.75/hr

As a core member of our Managed Services Practice (MSP), you will shift focus from project-based ... Experience with natural language processing (NLP) and conversational AI, including chatbot ...

This position reports into the Senior Manager, Security Engineering and will be based in our Austin ... than a chatbot. * Prompts as Code: Willingness to treat prompts and agent logic as version ...

This position reports into the Senior Manager, Security Engineering and will be based in our Austin ... than a chatbot. * Prompts as Code: Willingness to treat prompts and agent logic as version ...

This position reports into the Senior Manager, Security Engineering and will be based in our Austin ... than a chatbot. * Prompts as Code: Willingness to treat prompts and agent logic as version ...

Chatbot Manager information

See Austin, TX salary details

$27.3K

$81K

$136.3K

How much do chatbot manager jobs pay per year?

As of Aug 28, 2026, the average yearly pay for chatbot manager in Austin, TX is $80,959.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,600.00 and $115,500.00 per year, depending on experience, location, and employer.

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 Austin, TX?

The most popular types of Chatbot jobs in Austin, TX are:

What cities near Austin, TX are hiring for Chatbot Manager jobs?

Cities near Austin, TX with the most Chatbot Manager job openings:

Infographic showing various Chatbot Manager job openings in Austin, TX as of August 2026, with employment types broken down into 86% Full Time, 12% Part Time, and 2% Contract. Highlights an 79% Physical, 2% Hybrid, and 19% Remote job distribution, with an average salary of $80,959 per year, or $38.9 per hour.

Technical Solutions Delivery Manager

PayIt

Austin, TX • On-site

Full-time

Posted 29 days ago


Job description

PayIt is seeking a Technical Solutions Delivery Manager. You will own the path from client need to delivered service: understanding complex Motor Vehicle and Transportation business rules, shaping the solution approach, coordinating internal teams, managing risks and timelines, and helping create a repeatable delivery model across PayIt's DMV services vertical.

What You'll Be Doing:

Solution Design & Engineering Partnership

  • Partner closely with Engineering to translate client business rules, statutory requirements, and technical constraints into scalable platform solutions rather than one-off builds.
  • Perform platform configuration hands-on and use that configuration fluency to make better decisions on solution design and delivery upstream.
  • Pressure-test proposed solutions for reusability by identifying where a client-specific request can become a platform-level capability.

Delivery Ownership

  • Develop and manage implementation timelines end-to-end, including milestones, dependencies, risks, and go-live readiness criteria.
  • Track project status, risks, dependencies, issue mitigation, and go-live dates; maintain a single source of truth that internal teams and clients can trust.
  • Provide clear, decision-ready updates to internal leadership and client stakeholders, calibrated to each audience.

Client Leadership

  • Lead client technical and deployment calls with Engineering support, serving as the primary technical delivery voice with state agency stakeholders.
  • Build client confidence through clarity: translate platform behavior into business terms and client requirements into engineering terms.
  • Manage scope, expectations, and trade-off conversations directly with clients when requirements, timelines, and platform capabilities are in tension.

Cross-Functional Orchestration

  • Coordinate with Finance, Support, and Client Operations on financial setup, launch readiness, and post-launch handoff so go-lives land clean and stay clean.
  • Ensure post-launch ownership is unambiguous: every workflow, escalation path, and support process has a named owner before handoff.

Scale & Repeatability

  • Build the tools, playbooks, reporting cadences, and process improvements that turn DMV delivery from a bespoke effort into a repeatable operating model.
  • Codify what you learn: every implementation should make the next one faster, cheaper, and lower risk.

What You'll Need to Have:

Delivery & Solutioning Foundation

  • 4-6 years in technical implementation, solutions delivery, technical program management, or solutions consulting for a B2B SaaS platform, or an equivalent track record of owning complex technical delivery end-to-end.
  • Proven ability to take ambiguous, rule-heavy client requirements and turn them into shipped, working solutions. Government, financial services, healthcare, or other regulated-industry experience is a strong signal.
  • Working technical fluency: you can read an API spec, reason about integrations and data flows, understand configuration-driven platform architecture, and hold your own in engineering design conversations. You do not need to write production code, but engineers should trust your judgment. You must be comfortable with technical concepts like JSON, SQL, web services, and application logs. 
  • Structured project management instincts: You manage risks, dependencies, critical paths, and go-live readiness; use Jira or similar tools to track work, document ownership, and surface blockers; and provide updates that drive decisions and action.

Client-Facing Strength

  • Executive presence with technical stakeholders: you can lead a deployment call with a state agency team, handle hard questions in real time, and leave the client more confident than when the call started.
  • Skill in managing trade-off conversations: scope vs. timeline, custom vs. platform, now vs. right.

Collaborative Operating Style

  • You build trust quickly, communicate proactively, follow through on commitments, and work well across teams 

AI Fluency

  • Daily, fluent use of AI tools in your actual work today: documentation, analysis, planning, communication drafting, and research. 
  • A learning posture: the AI toolchain will look different in 12 months, and you are the kind of person who will be ahead of that curve rather than trained on it.

Bonus Points for:

  • GovTech, public sector, or DMV/motor vehicle domain experience, including familiarity with agency stakeholder dynamics, or statutory business rules.
  • Ability to design AI-enabled workflows, not just prompt a chatbot: you have built reusable prompts, automations, custom GPTs/agents/assistants, or AI-assisted processes that other people use.
  • Payments, financial reconciliation, or fintech delivery experience.
  • Hands-on experience with low-code automation platforms, scripting, or SQL for self-serve analysis.
  • Experience standing up delivery operations at a scaling company: you have built the machine, not just operated inside one.