Vice President of Engineering, SundaySky

• 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
• 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

Desirable

• 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
• 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