Remote Director, Quality Engineering — AI-Driven Testing

Humana

Boston (MA)

Remote

USD 157,000 - 215,000

Full time

15 hours ago

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Job summary

Humana seeks a strategic Director of Segment Quality Engineering to guide quality practices across a defined portfolio. You will lead QA strategy, automation, and release readiness, partnering with Product, Engineering, and Platform teams to embed quality throughout the software lifecycle.

You will mentor SDETs and engineers, establish KPI-driven governance, and drive AI-enabled quality innovations to improve speed, coverage, and reliability in a complex, regulated healthcare tech environment.

Qualifications

Bachelor's degree or equivalent experience.
10+ years of experience in software engineering, quality engineering, testing, or related technical disciplines.
5+ years of leadership experience managing quality engineering, test automation, or software delivery teams in large enterprise environments.
Experience leading quality engineering execution across multiple agile teams or a complex application/product portfolio.
Demonstrated success driving quality engineering modernization, including automation, tooling, process improvement, and metrics-driven execution.
Strong understanding of Agile, DevOps, and CI/CD practices.
Experience with API, UI, integration, regression, and end-to-end testing approaches.
Familiarity with distributed systems and modern application architectures.
Strong communication and stakeholder management skills, with the ability to influence cross-functional leaders.
Experience working in matrixed organizations and leading geographically distributed teams.
Proven experience leading adoption of AI capabilities within Quality Engineering processes.
Demonstrated success leveraging AI to improve test planning, test design, test automation, and QE effectiveness.
Experience utilizing AI-enabled solutions for: Test case generation and optimizationTest automation acceleration and maintenanceChange impact assessment and risk analysisRequirements traceability and coverage verificationRelease readiness and quality risk assessment
Experience establishing governance, metrics, and best practices for responsible and effective adoption of AI within Quality Engineering organizations.

Responsibilities

Lead quality engineering strategy and execution across a defined portfolio, domain, or segment.
Lead and develop quality engineering managers, leads, engineers, and SDETs; drive organization design, talent growth, and team performance.
Establish portfolio quality goals, KPIs, and governance to improve delivery quality, release readiness, and production stability.
Embed built-in quality across planning, design, development, testing, and deployment.
Oversee test strategy and execution across functional, integration, end-to-end, regression, and release validation.
Own portfolio-level quality risk management, including defect trends, release concerns, environment issues, and cross-team dependencies.
Drive automation-first practices and integrate quality signals, validation, and gates into CI/CD pipelines.
Lead adoption of AI-enabled quality engineering capabilities and promote innovative practices that improve speed, coverage, and reliability.
Sponsor modernization of quality frameworks, tooling, and test approaches for APIs, distributed systems, and cloud-native platforms.
Oversee non-functional quality practices, including performance, resiliency, operational readiness, and security validation.
Use metrics and production insights to drive continuous improvement, maturity, and investment priorities.
Partner with segment and enterprise stakeholders to align execution with broader quality engineering strategy, standards, and reference architecture direction.
Ensure responsible adoption of AI and compliance with applicable security, privacy, regulatory, and operational standards.