About Autonomize AI

The Opportunity

What You’ll Do

Quality Engineering & Leadership

• Strategic QA Leadership: Define, own, and execute the global QA vision, quality metrics (KPIs/OKRs), and long-term testing roadmap aligned with business objectives.
• Team Governance & Mentorship: Lead, mentor, and grow a high-caliber team of SDETs and QA engineers; drive continuous learning and establish engineering best practices.
• Automation & ML Testing: Oversee the architectural strategy for scalable, robust test automation frameworks (Web UI, API, Data Pipelines, and Machine Learning/AI model testing).
• Enterprise Quality Assurance: Drive shift-left testing methodologies, security/compliance validations, performance/load testing, and overall dark-data pipeline reliability.

Delivery & Release Management

• End-to-End Release Management: Own the release lifecycle for multi-tenant and enterprise AI deployments—managing release cadence, risk assessments, scope stability, and go/no-go decisions.
• CI/CD Pipeline Governance: Collaborate closely with DevOps and Engineering to integrate automated quality gates into CI/CD pipelines, enabling smooth, repeatable, zero-downtime deployments.
• Cross-Functional Delivery Alignment: Act as the central liaison between Engineering, Product Management, Customer Success, and Leadership to ensure delivery timelines are met without compromising quality.
• Incident & Risk Management: Establish post-release verification protocols, track production issues, lead root cause analyses (RCA), and implement preventive measures to continuously elevate delivery reliability.

You’re a Fit If You Have

• Experience: 12+ years of progressive experience in Software Quality Engineering, with 5+ years in a manager or leadership capacity.
• Release & Delivery Expertise: Proven track record in release management, release governance, and orchestrating complex deployment cycles for enterprise SaaS/Cloud platforms.
• Technical & Automation Mastery: Deep expertise in building/architecting test automation frameworks using Python, Selenium, PyTest, Cypress, or similar tools, along with API testing (Postman, REST Assured).
• AI/ML & Data Platform Exposure: Demonstrated experience testing data-intensive applications, unstructured data processing pipelines, or Machine Learning/AI platforms.
• CI/CD & DevOps Integration: Hands-on familiarity with CI/CD tools (e.g., GitHub Actions, GitLab CI, Jenkins) and containerized environments (Docker, Kubernetes).
• Process & Agile Leadership: Deep understanding of Agile/Scrum delivery models, test management systems (Jira, Xray/Zephyr), and tracking key quality metrics (Defect Escape Rate, Test Coverage, Release Cycle Time).
• Communication & Executive Presence: Outstanding stakeholder management, problem-solving skills, and the ability to articulate quality/release risks to technical and non-technical leaders alike.

What We Offer

• Influence & Impact: Shape the core quality and delivery strategy for enterprise AI implementations.
• Outsized Opportunity: Join at an influential level in a rapidly scaling, VC-backed startup.
• Ownership & Autonomy: End-to-end ownership of QA and release processes with the freedom to innovate.
• Learning & Growth: Constant exposure to serial founders, cutting-edge AI technologies, and a dedicated professional development budget.