Vice President of Engineering

Matilda Cloud is one of the most consequential platforms being built in cloud right now. We help enterprises do what most of them know they need to do but cannot figure out how to do well: assess complex multi-cloud estates, migrate workloads without breaking the business, modernize what is worth modernizing, and run all of it with intelligence baked in. Our platform pairs machine learning with real-time operational data to automate work that has historically required armies of consultants and months of risk. We are at an inflection point. The market is racing toward AI-augmented cloud operations and away from manual, ticket-driven IT. Our customers are looking for a partner who can move them through that shift safely, quickly, and with confidence. To meet that moment, we are hiring a Vice President of Engineering who will help us build the next chapter of this company. About the Role This is not a maintenance role. It is not a process-cleanup role. It is a build-the-future role. The Vice President of Engineering at Matilda Cloud is a hybrid leader — equal parts Director of Engineering and VP of Product Management. You will own how our platform is built, but you will also help decide what it becomes. You will shape engineering culture, scale the organization, and make the technical bets that determine whether Matilda Cloud is a great company or a category-defining one. This is a role for someone who has the operational discipline of a seasoned engineering executive and the creative ambition of a product founder. You will report to the CTO and serve as the operational and product engineering counterpart to the executive team. You will lead our distributed engineering and QA organization across Texas and India, partner directly with Product Management to set the roadmap, and be the face of engineering to customers, investors, and the board. Responsibilities Vision, Innovation, and Product Engineering Leadership Co-own product strategy alongside Product Management — translating customer pain, market signals, and emerging technology into a roadmap that is ambitious, technically credible, and commercially relevant. Bring a creative, opinionated point of view on what Matilda Cloud should build next, where the platform should expand, and which bets are worth making. Champion experimentation, prototyping, and rapid learning as core engineering disciplines — not as side projects. Represent engineering in executive, customer, investor, and board conversations with the polish of a product leader and the substance of a technologist. Cloud and Migration Mastery Bring deep, hands-on expertise across AWS, Azure, GCP, and OCI — the multi-cloud reality our customers live in and our platform was built to serve. Lead the engineering vision for cloud migration, modernization, and optimization — the heart of what Matilda Cloud does for our customers and what differentiates us in the market. Make architecture decisions that balance speed, scale, security, and cost across multi-tenant cloud environments — and ensure those decisions hold up under the scrutiny of enterprise buyers. Partner with customer-facing teams to translate real-world migration challenges into platform capabilities, then back into product roadmap. AI at the Forefront Set the strategy for how AI shows up in our product — not as a buzzword, but as a meaningful capability that compounds value for customers across assessment, migration, optimization, and ongoing operations. Build and operate the engineering capabilities needed to ship AI features responsibly: model integration, inference infrastructure, evaluation pipelines, drift monitoring, and graceful degradation when models underperform. Make Matilda Cloud one of the most AI-fluent engineering organizations in the cloud-modernization space — both in what we build and in how we build it. Lead the team's adoption of AI-assisted development (code generation, automated review, test synthesis, documentation) with clear governance, sensible guardrails, and a bias toward measurable productivity gain. Stay close to the frontier — actively tracking model releases, agentic patterns, and infrastructure shifts so the platform stays ahead, not behind. Engineering Excellence at Scale Build the operating system of our engineering organization — SDLC, sprint cadence, code quality standards, CI/CD, release management, and the metrics that make all of it visible. Take us from the informal, relationship-driven workflows of an early-stage team to a predictable, repeatable, scalable model that supports continued headcount and product growth. Mature our DevOps, automated testing, and release infrastructure so the team can ship confidently and frequently with reduced risk. Introduce engineering metrics (cycle time, lead time, defect escape rate, deployment frequency) and use them to drive continuous improvement, not to drive fear. Manage technical debt with discipline — knowing when to pay it down and when to live with it in service of velocity. People, Culture, and Growth Lead, mentor, and grow a distributed team of engineers and QA professionals across Texas and India — building a high-performance, inclusive, and energizing culture. Design organizational structures, career ladders, and performance frameworks that scale with the company. Partner with talent acquisition to recruit senior engineering talent and reduce single-point-of-knowledge risk. Be a visible, accessible leader who earns trust across the company — from junior engineers to the board. Coordinate cross-team dependencies between Texas and India pods with time-zone-aware handoffs, clean interfaces, and shared accountability. Qualifications 10+ years in software engineering with at least 4 years in senior engineering management, including direct management of managers. Deep, hands-on multi-cloud expertise across AWS, Azure, GCP, and/or OCI, with a credible track record of leading cloud migration, modernization, or large-scale infrastructure transformation programs. Demonstrated experience leading engineering organizations through the deliberate professionalization of engineering practices — you have personally designed and rolled out SDLC frameworks, code quality standards, agile delivery, and release management disciplines in environments where they did not yet exist. Meaningful AI experience in two dimensions: (1) you actively use AI-assisted development tools and have a clear point of view on where they accelerate engineering and #J-18808-Ljbffr