Vice President of Engineering

In July 2022, SundaySky completed a $100 million investment from the private equity firm Clearhaven Partners, providing capital for growth and innovation. This investment completes the transition of the business from a managed services company to a SaaS company, enabling the next stage of growth. Clearhaven is a Boston-based private equity firm focused exclusively on software and technology investments. Founded in 2019 by an investor-operator team with over 50 years of combined experience, Clearhaven was purpose-built to partner with differentiated, growth-stage software companies. The firm invests thematically in high-quality B2B software businesses, supporting management teams seeking an operationally focused partner to drive transformational growth.

SundaySky is positioned in an incredible market for personalized, enterprise video. The company represents an extremely attractive opportunity in a fast-growing market:

● Compelling financial profile

○ $25M+ revenue

○ 20%+ SaaS bookings growth 2025 vs 2024

○ EBITDA positive

○ 80 FTE globally

● Significant market opportunity

○ TAM for Enterprise Video Content Management

○ $48B+ TAM with a growing CAGR of 13% by 2030

○ 65% of businesses use videos for customer service, 61% of companies use videos for employee communications

○ Opportunity to activate moments that matter during the customer lifecycle through personalized video to drive real business outcomes

● Strong Customer Base

○ Blue chip customer base in banking, financial services and insurance

○ Leading banks and financial service firms such as Bank of America, Schwab, Morgan Stanley, T. Rowe Price, Ascensus, Broadview and Bread Financial

○ Health, commercial and property insurance firms including Chubb, Zurich America, Progressive, Liberty, Aetna, UnitedHealth Care, Anthem, Emblem, Kaiser Permanente , and Floriday Blue

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. The VP of Engineering will scale the team, strengthen technical ownership, improve delivery predictability, and establish a modern software development lifecycle powered by automation, AI-assisted development, quality engineering, and measurable execution rigor. The ideal candidate has successfully built and led distributed Engineering teams, modernized development practices, implemented AI-enabled workflows, and improved delivery velocity and quality. This is a player-coach role requiring the ability to contribute directly when needed through architecture, technical design, prototyping, complex problem-solving, and code.

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.