Vice President of Software Engineering

VP of Software EngineeringLocation: Riyadh Level: Executive / VPCompany Description Solidrange is a cybersecurity company based in Riyadh focused on building modern platforms to address cybersecurity and enterprise Governance, Risk, and Compliance (GRC) challenges. The company aims to transform the GRC technology landscape so organizations can modernize their practices and lower operational overhead. Solidrange’s mission is to reduce human-driven cybersecurity risks, simplify compliance and risk management, and support seamless business continuity. Team members work on solutions that directly impact how enterprises protect their assets and maintain resilience in a rapidly evolving threat environment. This is an opportunity to contribute to a high-impact domain at the intersection of cybersecurity, technology, and business operations.Role Description The Vice President of Software Engineering is a full-time, hybrid role based in Riyadh, with flexibility for some work from home. This role leads the engineering organization, setting technical direction, defining best practices, and ensuring delivery of secure, scalable, and reliable cybersecurity and GRC platforms. Day-to-day responsibilities include overseeing software development teams, collaborating with product management on roadmaps and priorities, and working with architecture leaders to define system design and technology standards. The VP will drive engineering execution, improve development processes, and establish metrics for quality, performance, and security. The role also involves partnering with executive leadership on IT strategy, resource planning, and budget, mentoring engineering leaders, and fostering an inclusive, high-performing culture aligned with Solidrange’s mission.Role OverviewWe are need a VP of Engineering who is first and foremost a deeply experienced software engineer someone who has spent years in the trenches building production systems and only then stepped into leadership. You still write code, review PRs with substance, and can out-architect any problem on the board. The title is VP, but the mindset is Senior Engineer who leads.What You'll Own·       Actively contribute to architecture, code reviews, and critical implementation decisions across .NET, Angular, FastAPI, Django and Python stacks·       Lead the design and hands-on delivery of AI capabilities: LLM integrations, agentic workflows, and RAG pipelines built into product features·       Own the technical roadmap alongside Product, translating business requirements into concrete, implementable engineering plans·       Set engineering standards from a place of experience code quality, CI/CD, security patterns, testing discipline and model them yourself·       Mentor and grow engineers across the team; your technical depth is what makes your feedback actionable·       Own reliability and scalability of enterprise-grade production systems , SLAs and uptime are your problem too, not just ops·       Make fast, well-reasoned build-vs-buy and architectural trade-off decisions without needing a committee·       Report to the executive team on engineering health with the credibility of someone who knows the codebase firsthandTechnical LeadershipArchitecture & Systems Design·       You have personally designed and shipped distributed systems, multi-tenant SaaS architectures, and enterprise integration patterns.·       Deeply comfortable across the full stack: .NET/C# backend services, Python/FastAPI microservices, Angular frontends, and cloud infrastructure·       You prototype to validate, write code to unblock, and review PRs with the depth to catch what automated tools missAI & Intelligent Systems·       You have built and shipped production AI features yourself LLM orchestration, RAG pipelines, agentic tool-use patterns.·       Can evaluate AI approaches for feasibility, latency, cost, and risk from implementation experience, not theory·       Understands the operational and compliance requirements of AI in enterprise environments: audit trails, explainability, data residency, prompt securityEnterprise Platform Engineering·       Proven track record maintaining and scaling enterprise SaaS products with demanding availability and security requirements·       Fluent in cloud-native patterns (Azure preferred), DevOps pipelines, containerization, and platform observability·       Experience with GRC or BCM domains, or adjacent regulated/compliance-heavy industries, is a strong advantageWhat We're Looking For·       12+ years of hands-on software engineering experience ,the majority of your career has been spent writing and architecting code, not managing it from a distance·       Actively coding or architecting within the last 2 years; we will ask about recent technical work in the interview process·       Deep, production-proven experience in at least two of: .NET/C#, Python/FastAPI, Angular with working familiarity across all of them·       Shipped AI features to production: LLM integrations, RAG pipelines, or agentic systems built on frameworks like LangChain, LlamaIndex, Semantic Kernel, or equivalent·       Strong grasp of enterprise software requirements: multi-tenancy, RBAC, SSO/SAML, audit logging, data isolation, and compliance controls·       Leadership experience that grew naturally from technical credibility·       Bachelor's or Master's in Computer Science, Engineering, or equivalent Education·       Bachelor's degree in Computer Science, Software Engineering, Information Technology, or a closely related field is required·       Master's degree in Computer Science, Software Engineering, with a strong technical focus is preferred·       Relevant certifications are a plus: Microsoft Azure (AZ-204, AZ-305, AZ-400), AWS Solutions Architect, Google Cloud Professional, or AI/ML certifications (e.g. DeepLearning.AI, Coursera ML Specialization)Nice to Have·       Experience in BCM, GRC, risk management, or adjacent compliance-driven SaaS verticals·       Familiarity with frameworks such as ISO 22301, ISO 27001, SOC 2, or NIST as they relate to product and engineering decisions·       Open-source contributions or a public portfolio of technical work·       Experience with AI safety, responsible AI practices, or AI governance in enterprise contexts·       Prior experience at a scale-up navigating the transition from startup to enterprise