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AI that actually understands healthcare is transforming operations, one workflow at a time.
The Role
Lead the global QA strategy, quality engineering roadmap, automation architecture, and software release governance for enterprise AI products. Manage and mentor SDETs and QA engineers, oversee testing across web, APIs, data pipelines, and ML models, and establish CI/CD quality gates. Own release schedules, risk assessments, go/no-go decisions, incident management, root cause analysis, and cross-functional delivery alignment while ensuring secure, reliable, high-quality deployments.
Summary Generated by Built In
About Autonomize AI
The Opportunity
What You’ll DoQuality Engineering & Leadership
You’re a Fit If You Have
What We Offer
Autonomize AI is on a mission to help organizations make sense of the world's dark data. Unstructured data contains critical insights that, when paired with human context, unlock transformative business outcomes. Our goal is to make that process effortless and accessible.
We are an ambitious, global, remote team committed to human-machine collaboration. Our founders are serial entrepreneurs who have successfully scaled multiple venture-backed companies. We combine expertise in building cutting-edge data products, captivating user experiences, and scaling enterprise AI solutions.
We are seeking a seasoned, strategic QA Manager with 12+ years of experience to build, scale, and govern our quality engineering and software release ecosystem.
In this dual-impact leadership role, you will define and execute the overall QA strategy while taking end-to-end ownership of delivery schedules, CI/CD release governance, and cross-functional release management. You will manage and mentor a team of high-performing SDETs and QA Engineers, ensuring our enterprise AI products are delivered predictably, securely, and with uncompromised quality.
What You’ll DoQuality 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.
- 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.
Autonomize AI is an equal opportunity employer and does not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.
Skills Required
- 12+ years of progressive experience in software quality engineering
- 5+ years of experience in a management or leadership capacity
- Experience with release management, release governance, and complex enterprise SaaS or cloud deployment cycles
- Expertise architecting test automation frameworks using Python, Selenium, PyTest, Cypress, or similar tools
- Experience with API testing using Postman, REST Assured, or similar tools
- Experience testing data-intensive applications, unstructured data processing pipelines, or AI/ML platforms
- Familiarity with CI/CD tools such as GitHub Actions, GitLab CI, or Jenkins
- Familiarity with Docker and Kubernetes containerized environments
- Understanding of Agile/Scrum delivery models
- Experience with test management systems such as Jira, Xray, or Zephyr
- Experience tracking quality metrics including defect escape rate, test coverage, and release cycle time
- Outstanding stakeholder management, problem-solving, and executive communication skills
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The Company
What We Do
Autonomize AI Agents & Copilots organize, contextualize and summarize unstructured data to reduce the administrative burden for healthcare knowledge workers to make data-driven decisions and improve patient outcomes. Our customers include health plans, providers and life sciences companies. Unlike generic AI systems retrofitted for healthcare, Autonomize deeply understands medical contexts, terminologies, and operational nuances. Our healthcare-focused AI Agents & Copilots augment knowledge work, drastically reducing administrative burden. Care management teams spend 78% less time per case, achieving an impressive 85% boost in case review efficiency. Prior authorization processes that traditionally take 20-30 minutes shrink to mere seconds, accompanied by an 80% reduction in manual errors, saving millions of dollars annually. Our AI Agents turn chaotic, unstructured healthcare data—clinical notes, PDFs, faxes, and claims—into structured, contextual information that informs decisions and actions. This has driven substantial real-world impact: organizations using Autonomize experience a 92% reduction in manual effort for care gaps and HEDIS chart reviews, dramatically improving compliance and STAR ratings. Autonomize AI is purpose-built for healthcare, transforming healthcare operations one workflow at a time through AI-native solutions that deliver immediate, scalable impact.
