Job Title: VP OF Engineering

Company: Matilda Cloud

Location: Richardson, TX (Hybrid)

About Matilda Cloud:

Matilda Cloud is at the forefront of AI-driven cloud management, delivering advanced solutions that simplify complex cloud operations, from multi-cloud assessments and seamless migrations to comprehensive optimization and modernization. Our platform integrates machine learning and real-time data insights to automate traditionally resource-intensive processes, enabling enterprises to scale their cloud environments efficiently and securely. By leveraging a modular yet interconnected suite of tools, we provide granular visibility and control over cloud infrastructure, helping businesses not only reduce costs but also meet stringent security, compliance, and performance standards.

The Vice President of Engineering is a pivotal leadership role, reporting directly to the CTO, responsible for defining and executing our engineering vision. This leader will shape how our teams operate, how our systems scale, and how our talent grows. This is a hands-on leadership role, equal parts strategic operator and servant leader.

Role Overview:

A central mandate of this role is establishing engineering excellence as a core organizational discipline. This is not a refinement project; it is a greenfield build. Specifically, you will be expected to design, scale, and institutionalize.

Responsibilities:

Leadership & Team Development

• Lead, mentor, and grow a distributed team of engineers and QA professionals across Texas and India, fostering a high-performance, inclusive culture.

• Build organizational structures, career ladders, and performance frameworks that scale with the company's growth.

• Partner with recruiting to attract senior engineering talent and reduce reliance on any single point of knowledge.

• Serve as a visible, accessible leader who earns trust at every level of the engineering organization.

Engineering Process Professionalization

• Own the end-to-end transformation of engineering practices from the informal, relationship-driven workflows of an early-stage team to a predictable, repeatable, and scalable operating model that can support continued headcount and product growth.

• Design and implement a mature SDLC: structured sprint ceremonies, definition-of-ready and definition-of-done standards, disciplined backlog management, and a clear path from feature request to production release.

• Establish engineering-wide standards for code quality including mandatory code review, branching strategies, test coverage thresholds, and documentation requirements, and build the culture of accountability that makes those standards stick.

• Build or significantly mature CI/CD pipelines, automated testing infrastructure, and release management processes that enable confident, frequent deployments with reduced risk.

• Introduce and institutionalize engineering metrics (cycle time, lead time, defect escape rate, deployment frequency) to create visibility into team health and delivery performance and use that data to drive continuous improvement.

• Balance rigor with practicality, implementing process improvements incrementally, with clear rationale, so that professionalization feels like an enabler rather than overhead to the engineering team.

AI-Augmented Engineering Operations

• Establish a forward-looking engineering culture that embraces AI-assisted development tooling as a standard part of how the team works including AI code completion, automated code review assistance, test generation, and documentation and build adoption norms that maximize productivity gains while preserving code quality and security standards.

• Develop and enforce clear policies around AI tool usage in the engineering workflow: what is sanctioned, what is off-limits given enterprise customer data obligations, and how AI-generated code is reviewed and validated before it enters production.

AI Feature Delivery & Engineering Partnership

• Partner closely with the Director of Product Management to evaluate the technical feasibility of AI-powered product features, providing honest assessments of data requirements, model complexity, latency constraints, and operational overhead before commitments are made.

• Build and maintain engineering capabilities required to deliver and operate AI features in production: model integration patterns, inference infrastructure, evaluation pipelines, monitoring for model drift, and graceful degradation when AI components underperform.

• Ensure the engineering team develops the skills and practices needed to build AI-enabled features responsibly including prompt engineering discipline, output validation, and customer-facing transparency standards appropriate for enterprise buyers.

Delivery & Execution

• Own delivery commitments across product engineering, providing CTO and stakeholders with reliable forecasts and clear escalation paths.

• Coordinate cross-team dependencies between Texas and India pods, ensuring time-zone-aware handoffs and alignment.

• Identify and eliminate systemic delivery blockers; create feedback loops that surface risk early.

Strategy & CTO Partnership

• Serve as the operational counterpart to the CTO and partner for Product Management through translating technical vision into executable roadmaps and team structures.

• Contribute to product and platform architecture decisions, balancing speed-to-market with long-term system health.

• Manage and reduce technical debt in a disciplined, prioritized manner as the product scales.

• Represent engineering in executive discussions, investor conversations, and customer-facing escalations as needed.

Qualifications:

• 10+ years in software engineering with at least 4 years in senior engineering management, including direct management of managers.

• Demonstrated, hands-on track record leading engineering organizations through the deliberate professionalization of engineering practices. This means you have personally designed and rolled out SDLC frameworks, code quality standards, agile delivery processes, and release management disciplines in an environment where these did not previously exist or were inconsistently applied. Stories of what you built, how you gained buy-in, and what measurably changed are expected in the interview process.

• Fluency with modern agile and lean delivery frameworks; strong opinions on what works at different stages of company growth and the judgment to adapt accordingly.

• Experience managing distributed, cross-cultural engineering teams; familiarity with US–India team dynamics is strongly preferred.

• Deep understanding of enterprise software development, including SaaS delivery models, multi-tenant architecture considerations, and release management.

• Hands-on experience establishing or maturing DevOps, CI/CD, and automated testing practices in a growing organization.

• Meaningful AI experience in both dimensions this role requires: (1) operations — you actively use AI-assisted development tools today, have a point of view on where they improve engineering throughput versus where they introduce risk, and have thought carefully about governance in an enterprise software context; and (2) product — you have led engineering teams that designed, built, and operated AI-powered features in production, and you understand the infrastructure, reliability, and validation challenges that come with it.

• Track record of building and retaining strong engineering teams; experience partnering with talent acquisition to scale headcount.

• Strong communication skills; able to translate complex technical topics for non-technical executives, customers, and board stakeholders.

Preferred Qualifications:

• Background as a software engineer or architect; ability to engage credibly in technical design discussions.

• Experience with enterprise B2B software, platform products, or multi-tenant SaaS environments.

• Deep familiarity with multiple cloud infrastructure environments (AWS, OCI, Azure, GCP) and infrastructure-as-code practices.

• Prior experience in a company scaling 150+ engineers.

• Computer Science, MBA or equivalent executive leadership experience is a plus.

Why Matilda Cloud?

• Matilda Cloud offers competitive compensation including base salary, performance bonus and equity in a high-growth company.

• A seat at the table, direct influence on product strategy, engineering culture, and company strategy.

• Hybrid work model from our Richardson, TX office with comprehensive benefits including health, dental, vision, 401(k) with match and PTO.

• We are an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

To apply, submit your resume to careers@matildacloud.com and a brief description on how you've led teams through engineering process transformation.