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Sr Specialist Quality​/M&P​/Process - AI Training Manager

Job in Richardson, Dallas County, Texas, 75080, USA
Listing for: AT&T
Full Time position
Listed on 2026-07-20
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), AI Evaluation, Data Analyst, Change Management
Salary/Wage Range or Industry Benchmark: 87200 - 130800 USD Yearly USD 87200.00 130800.00 YEAR
Job Description & How to Apply Below

This position requires office presence of a minimum of 5 days per week and is only located in the location(s) posted. No relocation is offered.

At AT&T, we empower leaders to drive change in a fast-evolving, connected world. Your strategic vision will help serve customers and transform lives through innovative solutions and impactful connections.

The Sr Specialist Quality/M&P/Process - AI Training Manager is responsible for overseeing the training, validation, and continuous improvement of Agentic Capabilities—AI-powered agents designed to autonomously process a variety of ticket types within workflow management systems. This role owns AI agent quality: ensuring reliable, high-quality outcomes; rapidly reviewing and resolving exception (“fallout”) tickets; applying corrections and re-ingesting updates; improving training data and fine-tuning artifacts;

updating the agent knowledge base; and rerunning tickets to validate fixes—continuously strengthening agentic capabilities.

Key Responsibilities Agentic Capability Management
  • Monitor the performance of Agentic Capabilities as they autonomously process various ticket types.
  • Ensure seamless integration of AI agents into new or existing workflows, optimizing for efficiency and accuracy.
Fallout Review & Correction
  • Review fallout tickets (cases where AI agents cannot resolve issues) within a workflow management tool.
  • Diagnose root causes, make necessary corrections, and re-ingest updated information to the AI system.
  • Ensure all fallout tickets are actioned within a 48-hour window; unresolved tickets revert to the human-worked queue.
Training & Continuous Improvement
  • Analyze fallout patterns to identify knowledge gaps, process inefficiencies, or opportunities for AI improvement.
  • Develop and implement training protocols to enhance Agentic Capabilities, leveraging prompt engineering, model validation, and knowledge base updates.
  • Collaborate with cross-functional teams (product, engineering, support) to align AI behaviors with business needs and compliance requirements.
Knowledge Base & Documentation
  • Maintain and update the agent knowledge base, ensuring accurate, current, and comprehensive content for AI agents.
  • Document training methodologies, ticket resolutions, and process improvements for knowledge sharing and auditing.
Quality Assurance & Compliance
  • Validate AI performance through systematic review, testing, and user/stakeholder feedback.
  • Ensure all processes comply with regulatory standards, ethical guidelines, and company policies.
Reporting & Communication
  • Track and report on key metrics: ticket resolution rates, fallout frequency, review turnaround times, and AI improvement outcomes.
  • Continuous Improvement practices
  • Communicate insights, best practices, and recommendations to stakeholders and leadership.
Skills & Qualifications
  • Understanding of the business function and M&Ps; align AI behavior with policy and process; plus knowledge of supported workflows and tools with experience operating the systems involved (e.g., ticketing/workflow platforms).
  • Strong analytical and problem-solving skills with meticulous attention to detail; proven root cause analysis (RCA) capability.
  • General AI literacy and understanding of agentic systems; basic prompt engineering (iteration, testing, versioning).
  • Ability to manage fallout within SLAs, triage tickets, and drive rapid resolution; strong prioritization in fast-paced environments.
  • Observability: proficiency with logs, metrics, dashboards, and alerts; define and track quality KPIs (accuracy, fallout rate, MTTR).
  • Basic scripting understanding to automate corrections, content re-ingestion, and validation workflows.
  • Knowledge base authoring and maintenance; clear documentation of training methods, resolutions, and changes for auditability.
  • Compliance/data privacy/ethical guidelines awareness; maintain auditable processes and change logs.
  • Effective communication: synthesize findings, report metrics, and present recommendations to stakeholders.
Preferred Skills
  • Advanced observability (distributed tracing, SLO/SLA design) and incident response practices.
  • Experiment tracking and ML operations tooling, feature flags, canary/rollback strategies.
  • F…
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