Product Engineer

🕒 vor 16 Tagen

🇵🇰 Pakistan – Remote

⏰ Vollzeit

🟡 Mittelstufe

🟠 Senior

🧑‍💻 Full-Stack-Entwickler

👻 Geisterscore 12%

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• Seit 16 Tagen offen.
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KnowledgeCity

WebsiteLinkedInAlle Stellen

201 - 500 Mitarbeiter

Gegründet 2007

👥 HR Tech

☁️ SaaS

📋 Compliance

HR Tech • SaaS • Compliance

KnowledgeCity ist eine KI-gestützte Plattform für die Workforce-Entwicklung. Sie kombiniert eine umfangreiche, mehrsprachige Trainingsbibliothek mit einem voll ausgestatteten Learning Management System sowie Modulen für Kurserstellung, Performance Management, Kompetenzbewertung und Kompetenz-Mapping, Sicherheits- und Compliance-Management, Phishing-Simulationen, SOP- und Richtlinienmanagement sowie Talentgewinnung und Onboarding. Die Plattform lässt sich in HRIS- und LMS-Systeme integrieren, automatisiert Compliance-Prozesse und Rezertifizierungen, erstellt KI-gestützte Kursinhalte und Assessments und unterstützt Analytics, mobile Apps sowie Integrationen für Enterprise Security. Sie richtet sich an HR-, Learning-&-Development- und Compliance-Teams in Organisationen verschiedenster Branchen.

Beschreibung

• 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.

🎯 Anforderungen

• 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.

🏖️ Vorteile

• 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.

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