Head of Engineering

This role is open within one of our portfolio companies, Quilr.Quillr is seeking an experienced Head of Engineering to drive research and development initiatives, spearhead customer-focused AI and security solutions, and serve as a technical ambassador between enterprise clients and our engineering teams. This role demands a proven track record of designing and implementing Python-based, AI-driven security frameworks in collaboration with customers, as well as the ability to translate complex real-world use cases into actionable product requirements.Key ResponsibilitiesLead hands-on proof-of-concept engagements with enterprise customers, demonstrating deep expertise in AI, and security domains. Translate customer pain points (e.g., data exfiltration, AI misuse, policy circumvention) into technical requirements and collaborate closely with product and engineering teams to ship new features. Conduct immersive on-site or virtual discovery workshops, technical deep dives, and architecture reviews to align product capabilities with each customer’s compliance, risk, and AI-adoption posture. Serve as the primary technical liaison: gather feedback, prioritize enhancements, and ensure customer requirements influence the product roadmap. Collaborate with data science and engineering teams to incorporate AI models into production-grade microservices, ensuring scalability, reliability, and security best practices. Design and deliver technical collateral, solution briefs, architecture diagrams, proof-of-concept scripts, test harnesses, that empower field teams and partners to demonstrate Quillr’s value proposition. Lead quarterly “Innovation Days” or similar working sessions where product, engineering, and customers co-develop advanced AI rule sets, detection logic, or policy engines. Work closely with Partners, Marketing, and Sales Engineering to create up-to-date demonstrations, whitepapers, and reference architectures. Provide structured, data-driven feedback to product management and engineering to drive roadmap decisions, feature prioritization, and overall product strategy.QualificationsMinimum Experience 15+ years in enterprise cybersecurity roles, with at least 5 years in a customer-facing technical leadership capacity and 1 year in AI/ AI-security. Hands-on experience building Python-based AI or machine-learning solutions (e.g., risk scoring engines, anomaly detection, NLP pipelines) in production environments. Proven track record of leading field R&D initiatives, delivering proof-of-concepts, reducing pilot-to-production timeframes, and translating client requirements into shipped features.Technical Skills Advanced proficiency in Python (including data-science libraries such as pandas, scikit-learn, TensorFlow/PyTorch, or similar). Strong background in AI and machine learning: model development, training, inference, and evaluation—preferably in security or risk-analysis contexts. Deep understanding of security frameworks and controls (e.g., DLP, SIEM, SOAR, UBA, XDR) and experience integrating them into AI workflows. Hands-on experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and CI/CD pipelines. Familiarity with compliance standards (e.g., SOC 2, ISO 27001, HIPAA, GDPR) and the ability to perform architecture reviews against those benchmarks.Leadership & Communication Exceptional written and verbal communication skills, capable of articulating complex technical concepts to both technical and executive audiences. Demonstrated ability to host technical workshops, lead cross-functional “Innovation Days,” and build structured feedback loops. Experience managing or mentoring small teams of SMEs, data scientists, or security engineers through technical initiatives.Education & Certifications Bachelor’s or Master’s degree in Computer Science, Computer Engineering, or related field. Advanced certifications preferred (e.g., GIAC, CISSP, SANS courses in AI security, cloud security architecture).Preferred Qualities Customer-Obsessed Mindset: You proactively seek to understand customer challenges, tailor solutions to their unique environments, and measure success by customer outcomes. Innovator at Heart: You relish pushing the boundaries of AI and security, pilot new technologies, and contribute to thought leadership in the space. Data-Driven Decision-Maker: You leverage analytics and customer feedback to continuously improve product features, streamline processes, and demonstrate measurable value. Collaborative Team Player: You thrive in a cross-functional environment, partnering with product, marketing, and engineering to ensure customer voice is embedded in all stages of development.