Quality Engineer

Responsibilities

• Lead initiatives that span multiple engineering teams and organizational boundaries.
• Translate broad business objectives into actionable roadmaps.
• Identify systemic causes behind recurring quality, release, or operational challenges.
• Drive sustainable solutions rather than temporary fixes.
• Define quality engineering strategies, standards, and architectures.
• Guide teams on test strategy, automation, release quality, observability, test environments, and risk management.
• Review designs, frameworks, and implementation approaches.
• Influence architecture decisions through a quality and reliability lens.
• Identify and implement opportunities to leverage AI across the software development lifecycle.
• Evaluate emerging AI capabilities and determine practical applications.
• Improve engineering productivity, test effectiveness, and delivery speed through AI-assisted workflows.
• Promote responsible and measurable AI adoption.
• Investigate complex technology, process, and organizational issues.
• Challenge assumptions and drive root-cause analysis.
• Create consensus among diverse stakeholders.
• Create clarity where none exists.
• Partner with Engineering, Product, Architecture, SRE, Release Management, and Quality Engineering leaders.
• Mentor senior engineers and technical leads.
• Lead through influence rather than authority.
• Elevate engineering practices across the organization.

Qualifications

• 10 years in software engineering, quality engineering, platform engineering, or related technical disciplines.
• Experience leading large-scale technical initiatives without direct authority.
• Strong understanding of modern software delivery practices and distributed systems.
• Experience defining test strategies across multiple test levels.
• Deep understanding of automation frameworks and CI/CD practices.
• Knowledge of release quality, risk assessment, defect prevention, and production readiness.
• Demonstrated experience applying AI tools to engineering workflows.
• Ability to evaluate AI opportunities beyond simple code generation.
• Understanding of strengths, limitations, risks, and governance considerations associated with AI-assisted engineering.
• Must be able to review code effectively, review automation frameworks and technical designs, evaluate architectural tradeoffs, and guide engineering teams without becoming the primary implementer.

Skills

• Technical depth and systems thinking.
• Organizational influence and leadership through coaching and technical leadership.
• Relentless curiosity and ability to solve ambiguous problems.
• Able to drive transformational quality engineering outcomes.

Pay

The typical base pay for this role across the U.S. is: $55.00 - $60.00 /hour. Non-exempt positions are eligible for overtime at a rate of 1.5 times the base hourly rate for all hours worked in excess of 40 in a work week, or as required by state or local law.

Benefits

Full-time employees are eligible to select from different benefits packages. Packages may include medical, dental, and vision benefits, health savings accounts with qualified medical plan enrollment, 10 paid days off, 3 days paid bereavement leave, 401(k) plan participation with employer match, life and disability insurance, commuter benefits, dependent care flexible spending account, accident insurance, critical illness insurance, hospital indemnity insurance, accommodations and reimbursement for work travel, and discretionary performance or recognition bonus. Sick leave and mobile phone reimbursement provided based on state or local law.