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How much do full time ai tutor xai jobs pay per hour?

As of Sep 6, 2026, the average hourly pay for full time ai tutor xai in the United States is $20.22, according to ZipRecruiter salary data. Most workers in this role earn between $14.42 and $24.04 per hour, depending on experience, location, and employer.

What is a full time AI tutor XAI?

A Full Time AI Tutor XAI is a professional specializing in educating others about artificial intelligence (AI) with a focus on Explainable AI (XAI). Their role involves teaching students, professionals, or organizations how AI systems work, how to interpret AI decisions, and the importance of transparency in AI models. They may develop educational materials, conduct workshops, and provide one-on-one or group instruction. Additionally, they help bridge the gap between complex AI technologies and users by making AI concepts more understandable and accessible.

What are the key skills and qualifications needed to thrive as a full time AI tutor XAI?

To thrive as a Full Time AI Tutor specializing in Explainable AI (XAI), you need a strong background in computer science, machine learning concepts, and a deep understanding of XAI methodologies, often supported by relevant degrees or certifications. Familiarity with tools like TensorFlow, PyTorch, SHAP, LIME, and data visualization platforms is typically required. Excellent communication, problem-solving skills, and the ability to simplify complex technical concepts for diverse audiences set top performers apart. These skills ensure effective education, foster trust in AI systems, and empower users to make informed decisions based on AI outputs.

What are some typical challenges faced by full time AI tutors specializing in explainable AI (XAI), and how can they overcome them?

Full Time AI Tutors in XAI often encounter the challenge of translating complex machine learning concepts into clear, accessible explanations for a diverse audience. They must stay updated on rapidly evolving XAI techniques while adapting their teaching methods to cater to different learning styles. Collaborating with data scientists, engineers, and non-technical stakeholders is common, requiring strong communication and interdisciplinary skills. Overcoming these challenges involves continuous learning, leveraging interactive tools, and fostering open dialogue to ensure learners truly grasp the principles of explainable AI.

What is the difference between Full Time Ai Tutor Xai vs Part Time Ai Tutor Xai?

AspectFull Time Ai Tutor XaiPart Time Ai Tutor Xai
Work HoursTypically 35-40 hours per weekLess than 20 hours per week
CredentialsRequires relevant certifications in AI and tutoringMay require similar certifications but with less emphasis
Work EnvironmentFull-time employment, often in educational institutions or online platformsFlexible, often freelance or part-time online roles
Employer UsageEmployed by educational companies or institutionsOften contracted or freelance roles with multiple clients

Full Time Ai Tutor Xai typically involves a standard workweek with stable employment, while Part Time Ai Tutor Xai offers flexible hours and freelance opportunities. Both roles require relevant AI and tutoring certifications, but full-time positions often demand more consistent availability and employer commitment.

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Infographic showing various Full Time Ai Tutor Xai job openings in the United States as of August 2026, with employment types broken down into 76% Full Time, 20% Part Time, and 4% Contract. Highlights an 66% Physical, 4% Hybrid, and 30% Remote job distribution, with an average salary of $42,053 per year, or $20.2 per hour.

Senior Manager, Support Operations (AI & BPO)

Amira Learning

Remote

Full-time

Re-posted 28 days ago


Job description

Senior Manager, Support Operations (AI & BPO)

Location: Remote-US 

Employment Type: Full-Time Reports to: Director of Scaled Success

About Amira Learning

Amira Learning accelerates literacy outcomes by delivering the latest reading and neuroscience with AI. As the leader in third-generation edtech, Amira listens to students read out loud, assesses mastery, helps teachers supplement instruction, and delivers 1:1 tutoring. Validated by independent university and SEA efficacy research, Amira is the only AI literacy platform proven to achieve gains surpassing 1:1 human tutoring.

Trusted by more than 2,000 districts and working in partnership with twelve state education agencies, Amira is helping 3.5 million students worldwide become motivated and masterful readers.

The Role

Amira's Support function is small, the BPO partner is mid-onboarding, and our chatbot needs work. We are hiring a Senior Manager, Support Operations to own end-to-end frontline support - Tier 0 (our AI chatbot) and Tier 1 (our BPO team) - and to operate the whole thing as an AI-native function.

We are not hiring a BPO manager who is curious about AI. We are hiring someone for whom AI is the substance of the work - writing prompts, building agent-assist tooling, analyzing tickets at scale, integrating systems with MCP, and continuously improving how our chatbot deflects and resolves. The BPO team is one of the things they operate, alongside and through these AI surfaces. The right person treats every operational question - staffing, QA, escalations, knowledge gaps - as something to investigate with data and improve with code, not something to manage through spreadsheets and meetings.

What You'll Own

Tier 0 - The Amira Chatbot


Continuously improve our customer-facing chatbot: prompt engineering, knowledge base curation, intent and entity tuning, escalation logic

  • Track and improve containment rate, deflection rate, and CSAT for chatbot-handled interactions
  • Build the diagnostic trees, agent flows, and fallback handling that make the chatbot trustworthy at scale
  • Iterate weekly, not quarterly

Tier 1 - The BPO Operation


Own the day-to-day relationship with our BPO partner, including agent-level performance management, QA calibration, and SLA accountability

  • Run the operational rhythm: weekly syncs, monthly reviews, quarterly business reviews
  • Build agent-assist tooling (LLM-powered response drafting, knowledge retrieval, ticket categorization, escalation routing) that makes our BPO agents materially faster and more accurate
  • Drive coaching and quality by using AI to analyze 100% of tickets - not 10% samples

System Integrations


Build and maintain MCP connectors wiring AI tools into our operational systems (Salesforce, Zendesk, ChurnZero) so AI agents can read and act on real data

  • Personalize agent-assist responses with customer context pulled from CRM and product data
  • Design integrations that respect FERPA obligations and the sensitivity of educator and student data

Analytics & Continuous Improvement

  • Run AI-driven analysis of ticket volume, contact drivers, sentiment, and resolution patterns
  • Translate analysis into concrete improvements: knowledge base updates, chatbot tuning, training topics for BPO agents, product feedback for Engineering
  • Build reusable dashboards and reporting that make support performance legible to the rest of the company

FERPA & Compliance

  • Apply FERPA and COPPA rigor to every AI system you build - guardrails, audit logs, human-in-the-loop where student data is in play
  • Own agent background-check and approval workflows for BPO personnel with access to student PII
How You'll Work

This is a builder's role. Expect to spend significant time:

  • In Claude Code, Cursor, Copilot, Codex, or equivalent - writing prompts, agent flows, integration code, analysis scripts. Daily, not occasionally.
  • With AI coding agents as a working partner, not a curiosity
  • Reading tickets, transcripts, and customer conversations - at scale, with AI assistance, looking for patterns no spreadsheet would catch
  • Building agent-assist tooling and MCP connectors - and shipping them iteratively
  • In Salesforce, Zendesk, the chatbot platform, and our data layer - comfortable enough to investigate, query, and modify directly

If you've never written a prompt, configured an MCP connector, or sketched an agent flow, this role will be a hard ramp. If you do these things daily already, you'll feel at home.

What You'll Bring

We're hiring against demonstrated work, not credentials.

Required

  • You have built and shipped AI-powered support tooling that real people use - agent-assist features, LLM-powered ticket analysis, chatbot improvements, or similar. We will ask you to walk us through what you built and how.
  • You have hands-on experience writing prompts as a working practice - for production systems, not personal experiments
  • You have integrated AI tools with operational systems (CRM, helpdesk, data warehouse) via MCP, APIs, or equivalent
  • You have worked in a customer support or customer experience function - running queues, owning SLAs, working with vendor teams, or analyzing tickets at scale
  • You are comfortable in code: reading it, writing it with AI assistance, debugging it when it breaks. No specific language requirement.
  • You can have a direct conversation with a frustrated customer or district administrator without losing your composure