QA Lead (AI-Powered Contact Center & Agentforce Solutions)

Key Responsibilities

QA Strategy & Leadership

• Be the primary quality advisor embedded in design, planning, and delivery—surface risks early, not late
• Lead and mentor the QA team while staying hands-on in complex Contact Center and IVR testing scenarios
• Own QA program delivery end-to-end: resource planning, test strategy, defect triage, environment coordination, and release readiness
• Define and track Contact Center-specific quality KPIs—test coverage for call flows, automation ROI, first-call resolution testing, and cycle time
• Design test strategies for multi-channel interactions (voice, chat, SMS), agent workflows, and failover scenarios
• Lead go-live readiness assessments and hypercare support—triage production issues quickly and maintain a known issues log
• Report quality status to steering committees and program reviews, framing risks in business impact (SLA, customer satisfaction, call abandonment)
• Partner early with Product and Engineering so quality ownership spreads across the organization, not just QA
• Apply sampling strategies, accuracy benchmarking, and prompt regression testing to validate LLM-powered and Agentic AI features; leverage GenAI tools to accelerate test case generation, documentation, and overall QA productivity

Test Design & Execution

• Author detailed, scenario-based test cases and traceability matrices covering functional, integration, regression, and UAT cycles
• Write thorough negative, boundary, and edge-case scenarios across IVR, chat bot, and customer service workflows — not just happy-path coverage
• Lead exploratory testing for complex, ambiguous workflows, applying risk-based judgment to prioritize coverage where business impact is highest
• Validate speech application (IVR) design — call flows, DTMF and speech recognition, routing logic, self-service menus, authentication, and error/timeout branches
• Validate chat bot and conversational AI behavior — intent recognition, escalation/handoff to live agents, knowledge grounding, and response accuracy
• Own end-to-end testing of integration layers — API request/response validation, middleware transformations, screen pops, and data sync across connected systems
• Lead SIT, E2E, UAT, regression, and go-live testing activities across release cycles
• Facilitate UAT readiness sessions with business stakeholders, supporting non-technical users and driving structured sign-off
• Own the full defect lifecycle — creation, triage, prioritization, SLA tracking, root cause tagging, and trend analysis
• Produce defect health reports and quality metrics summaries for leadership and stakeholders

Required Qualifications

• 8-10 years of hands-on experience leading QA or testing teams
• Hands-on experience testing speech applications (IVRs), chat bots, and other customer service tools
• Experience working within the call center/contact center ecosystem, with a solid understanding of customer service operations
• Demonstrated ability to lead QA across functional, integration, regression, UAT, and go-live testing cycles
• Experience building or scaling a QA program, including test strategy, governance, and reporting
• Strong communication skills — able to represent QA status and risk to both technical and non-technical stakeholders

Preferred Qualifications

• Experience with AWS, particularly Amazon Connect (IVR, Lex, Contact Flows, Lambda, Contact Lens)
• Experience with Five9, Genesys, Nuance, other telephony technologies being migrated into AWS or Service Cloud Voice
• Experience with Salesforce, particularly Service Cloud and Service Cloud Voice
• Exposure to conversational AI / GenAI validation — accuracy, hallucination checks, prompt/response quality, guardrails
• Familiarity with telephony fundamentals — ACD/routing, PSTN/toll-free/DID mapping, call recording and transcription

Tools & Technical Skills

• Test Management & Planning – Jira/Xray, Azure DevOps, Zephyr Scale, TestRail, or qTest
• Defect Tracking & Governance – Jira for end-to-end defect lifecycle management
• CI/CD & DevOps-Aware Testing – Jenkins, GitHub Actions, or Azure DevOps; Git-based version control (GitHub, GitLab, or Bitbucket)
• Test Automation & Performance Testing – UI automation for functional/regression coverage; API testing (Postman, REST Assured, or SoapUI); performance/load testing tools
• Speech / IVR Testing – experience with tools such as Empirix Hammer or Cyara a plus
• GenAI & Productivity Tools – Claude, Copilot, or ChatGPT for test case generation, test data creation, and QA documentation
• Reporting & Collaboration – Confluence, Slack, Microsoft Teams, Google Drive, and SharePoint

Soft Skills & QA Leadership

• Trusted Advisor Presence — Earns client confidence through expertise, transparency, and consistent delivery; comfortable challenging scope and requirements constructively when testability or clarity is lacking
• Radical Ownership — Takes full accountability for quality outcomes across the program; doesn't wait to be told what to test next and never passes the problem to someone else
• Hands-On Leadership — Leads by doing; equally comfortable mentoring junior team members and personally drafting and executing test cases on the same day
• Proactive Risk Management — Anticipates quality risks, raises blockers early, and brings solutions — not just problems — to every stakeholder conversation
• Composed Under Pressure — Navigates defect escalations, client concerns, and delivery conflicts with professionalism, sound judgment, and a calm, steady presence
• Intellectually Curious — Invests time to deeply understand the business process being tested, not just the technical specification; asks the right questions before writing the first test case
• Comfortable with Ambiguity — Makes risk-based quality decisions and writes meaningful test cases even when requirements are incomplete or evolving
• Finisher Mentality — Drives every test cycle through to formal sign-off and release; not someone who starts strong and disengages before the finish line
• Clear Communicator — Articulates QA status, risks, and recommendations clearly and confidently to both technical teams and non-technical business stakeholders
• Collaborative Coach — Develops junior QA team members, supports client UAT efforts, and fosters a quality-first culture across the entire program team