Vice President of Engineering

Vice President Of Engineering

SundaySky is a category-defining SaaS platform that enables enterprises and upper mid-market organizations to deliver highly personalized video experiences at scale across the entire customer lifecycle. The company represents an extremely attractive opportunity in a fast-growing market with a compelling financial profile, significant market opportunity, and a strong customer base.

We are seeking a Vice President of Engineering to lead the next stage of our product and platform growth. This executive will build and lead a scalable, high-performing, AI-enabled Engineering organization that delivers with speed, quality, accountability, and technical excellence.

Responsibilities

• Build, lead, and scale a high-performing Engineering organization across U.S.-based, nearshore, and offshore teams.
• Define the Engineering operating model, organizational structure, ownership boundaries, technical leadership model, and delivery expectations.
• Recruit, develop, and retain Engineering leaders, architects, full-stack engineers, QA professionals, DevOps resources, and technical leads.
• Create a culture of accountability, urgency, collaboration, craftsmanship, technical excellence, and continuous improvement.
• Establish clear performance expectations, career paths, Engineering standards, team health metrics, and leadership development plans.
• Design team structures that promote focus, accountability, technical depth, and scalable product development.
• Build an effective blend of employees and delivery partners to increase capacity, flexibility, and execution speed.
• Establish strong onboarding, documentation, knowledge-sharing, code ownership, architecture review, and technical readiness practices.
• Create repeatable processes for planning, delivery, support, technical decisions, and cross-functional coordination.
• Partner with Product, Customer Success, Sales, Operations, Finance, HR, and executive leadership to align resources with company priorities.
• Design and implement an AI-enabled software development lifecycle that improves productivity, quality, speed, and developer experience.
• Operationalize AI-assisted tools for coding, testing, documentation, code review, refactoring, debugging, requirements interpretation, release readiness, and production support.
• Integrate human technical judgment and AI acceleration across planning, architecture, development, testing, deployment, monitoring, and incident response.
• Establish responsible AI development standards covering security, intellectual property, privacy, code review, test coverage, architectural consistency, and human accountability.
• Partner with Product and UX to structure requirements, designs, and acceptance criteria for effective AI-assisted development.
• Develop internal Engineering agents, accelerators, automation, and workflows that reduce manual work and improve throughput.
• Provide technical leadership for AI-powered product capabilities, platform services, internal tools, and customer experiences.
• Evaluate opportunities involving AI, automation, agents, LLM integrations, personalization, recommendations, content generation, and intelligent workflows.
• Partner with Product Management to assess feasibility, architecture, cost, scalability, risk, and customer value.
• Guide the architecture of AI capabilities, including model integrations, prompt orchestration, data pipelines, APIs, permissions, observability, auditability, and human-in-the-loop workflows.
• Ensure AI features meet appropriate quality, security, privacy, compliance, monitoring, explainability, and governance standards.
• Help move the company from AI experimentation to repeatable, production-grade capabilities.
• Drive consistent, predictable, high-quality delivery across teams and initiatives.
• Establish operating rhythms for planning, estimation, dependency management, technical reviews, release readiness, and executive reporting.
• Implement automation-first practices across CI/CD, testing, QA, observability, security scanning, infrastructure provisioning, deployment, and release management.
• Improve speed by reducing rework, strengthening requirements readiness and technical design, and creating clear ownership.
• Define and track metrics such as cycle time, deployment frequency, lead time, defect escape rate, test coverage, production incidents, reliability, capacity, and release predictability.
• Establish clear definitions of ready and done, automated quality gates, disciplined release practices, and measurable success criteria.
• Create rapid feedback loops using customer input, production usage, support issues, incidents, and post-release data.
• Translate company and product strategy into a scalable technical strategy and execution roadmap.
• Lead architecture, platform scalability, reliability, security, performance, data, APIs, integrations, DevOps, AI enablement, and technical debt management.
• Align Engineering investments with business outcomes, revenue priorities, customer commitments, enterprise readiness, and long-term platform health.
• Establish architecture review practices that support speed, consistency, extensibility, maintainability, security, and resilience.
• Balance near-term delivery priorities with long-term technical sustainability.
• Create visibility into Engineering capacity, allocation, delivery status, dependencies, risks, and tradeoffs.
• Manage budgets, hiring plans, contractor spend, vendors, software tooling, infrastructure costs, and resource allocation.
• Identify and mitigate operational, security, scalability, architectural, delivery, personnel, compliance, and platform risks.
• Establish effective incident management, production support, monitoring, alerting, reliability, and postmortem practices.
• Ensure Engineering processes support security, privacy, compliance, auditability, enterprise.
• Contribute directly to architecture, technical design, prototyping, troubleshooting, and implementation when needed.
• Guide critical technical decisions, architecture proposals, design patterns, code quality standards, and Engineering tradeoffs.
• Serve as an escalation point for complex platform, scalability, reliability, performance, integration, data, and security challenges.
• Work directly with engineers to unblock delivery and model strong Engineering practices.

Requirements

• 10+ years of Engineering leadership experience, including leadership of managers, architects, technical leads, and distributed teams.
• Experience as a VP of Engineering, Head of Engineering, Senior Director of Engineering, or equivalent leader within a SaaS, enterprise software, platform, or technology company.
• Demonstrated success building, restructuring, scaling, and leading high-performing Engineering organizations.
• Strong full-stack background spanning frontend, backend, APIs, data, cloud infrastructure, and integrations.
• Hands-on software development experience and the ability to contribute to architecture, prototypes, technical design, code, and critical problem-solving.
• Strong architectural judgment across scalable systems, cloud-native platforms, data models, security, observability, reliability, and performance.
• Experience managing onshore, nearshore, and/or offshore teams and partners.
• Proven success improving Engineering operating models, delivery practices, technical ownership, velocity, and predictability.
• Experience implementing automation across CI/CD, testing, infrastructure, observability, security, quality gates, and release management.
• Experience adopting and operationalizing AI-assisted Engineering tools and workflows.
• Experience building AI-powered features, internal accelerators, workflow automation, LLM-enabled capabilities, or intelligent developer tools.
• Ability to partner effectively with Product, UX, GTM, Customer Success, Finance, HR, and executive leadership.
• Excellent communication skills, including the ability to explain technical strategy, risks, architecture, capacity, and tradeoffs to executive and board audiences.
• Strong judgment, urgency, accountability, and the ability to lead through ambiguity, growth, and change.

Preferred Qualifications

• Experience in B2B SaaS, enterprise software, marketing technology, fintech, financial services, insurance, or another regulated industry.
• Experience with tools such as GitHub Copilot, Claude Code, Cursor, or similar AI-assisted development platforms.
• Experience delivering capabilities involving LLMs, agents, prompt orchestration, personalization, recommendations, content generation, workflow automation, or intelligent analytics.
• Experience building organizations that use nearshore, offshore, contractor, or global delivery models.
• Experience with cloud-native, API-first, data-driven, multi-tenant, configurable, or enterprise-grade platforms.
• Experience improving organizations with limited roadmap visibility, backlog discipline, technical ownership, delivery accountability, or release predictability.
• Experience implementing automated regression and performance testing, security scanning, observability, and production-readiness practices at scale.
• Experience in a growth-stage company balancing customer commitments, platform modernization, technical debt, team scaling, and product innovation.