Product Engineer

• Own the complete lifecycle of an assigned product domain, from discovery and specification through design, engineering, QA, documentation, deployment, and continuous improvement.
• Direct and orchestrate a full suite of AI agents across all delivery disciplines while maintaining visibility and control over outputs.
• Deliver production-ready improvements continuously with quality-first release discipline.
• Conduct post-deployment validation within one hour of every production release using core workflows, admin journeys, edge cases, and live production data.
• Monitor deployment health, detect regressions, and initiate rollback when production stability is at risk.
• Ensure enterprise-grade release readiness, cross-environment testing, rollback readiness, and deployment quality tracking.
• Own UX quality and customer-facing workflow evaluation, including regular AI-assisted UX audits.
• Ensure user guides, API documentation, and operational notes ship with every feature.
• Proactively communicate risks, blockers, scope changes, forecasts, release coordination updates, and post-deployment status to the Program Delivery Manager or Head of Product.
• Prioritize work based on customer outcomes, business value, user satisfaction, support ticket reduction, and feature adoption.
• Maintain a prioritized improvement backlog using support tickets, QA audits, UX findings, usage analytics, and stakeholder feedback.

• 5+ years of hands-on experience in product management, engineering management, or a closely related discipline - with demonstrated ability to own and deliver end-to-end product outcomes independently.
• Proven track record of shipping real, production-grade products end-to-end - not just features within a larger team structure.
• Background spanning at least two of: software engineering, product management, UX design, or QA - with the ability to operate credibly across the full product lifecycle.
• Hands-on experience with AI-assisted development tools and a strong understanding of how to direct and review AI-generated output at production quality.
• Demonstrated experience owning production outcomes - including post-deploy validation, regression management, incident response, and deployment health monitoring.
• Experience evaluating and improving customer-facing workflows and UX quality - not limited to technical implementation alone.
• Background in agile, high-velocity delivery environments with a strong bias for continuous, quality-first delivery rather than batch-release cycles.
• Familiarity with database performance fundamentals (query optimization, indexing, execution planning) is a strong plus.
• EdTech or SaaS product experience preferred but not required.
• Bachelor's degree in Computer Science, Software Engineering, or a related technical discipline required.
• Master's degree preferred.
• Certified Scrum Product Owner (CSPO) or an equivalent Product Management certification.
• Full product lifecycle ownership: strategy, discovery, design, engineering, QA, documentation, deployment, and post-release validation - independently and at pace.
• Production accountability mindset: you own what ships, you own what breaks, and you fix it - without escalating raw problems or waiting for direction.
• Customer workflow thinking: ability to evaluate product experiences from a real user's perspective, not just a technical implementation standpoint.
• Enterprise delivery discipline: release governance, cross-environment testing, rollback readiness, deployment quality tracking, and stability assurance.
• AI agent direction: operates and orchestrates AI agents as high-output delivery partners - not as a crutch. Reviews every output critically before it touches production.
• Product intuition: strong instinct for what to build, why it matters to users, and how to connect engineering decisions to business outcomes.
• Proactive communication: surfaces risks and blockers early, communicates delivery status clearly, and escalates with solutions - not questions.
• Systems thinking: understands how their domain connects to the broader product ecosystem and considers upstream and downstream impact before making changes.
• Self-managing execution: operates with minimal supervision, unblocks independently, and holds a consistently high quality bar without external enforcement.
• Advanced English proficiency, both written and spoken, is mandatory for effective communication with partners and clients.

• High autonomy and direct domain ownership - you run your product, not a ticket queue.
• Work at the frontier of AI-native product engineering.
• Paid time off and a supportive, high-trust team environment.
• Opportunities for professional growth through access to training materials and company courses.
• Competitive compensation commensurate with experience.