Vice President of Engineering

SundaySky•New York, NY

4d•Remote

About The Position

SundaySky is seeking a Vice President of Engineering to lead the next chapter of its Engineering organization. This critical leadership role is responsible for building and leading a high-performing, scalable, AI-enabled Engineering function that can deliver with speed, quality, accountability, and operational discipline. The VP of Engineering will lead the transition of the Engineering organization to a new operating model, including building and scaling a U.S.-based Engineering team supported by nearshore and offshore talent. This leader will be responsible for ensuring business continuity during the transition, preventing knowledge loss, establishing strong delivery practices, and creating a modern software development lifecycle powered by automation, AI-assisted development, quality engineering, and measurable execution rigor. This role requires a hands-on, change-oriented Engineering executive who can operate strategically while also driving execution at the ground level. The ideal candidate has successfully built and led distributed Engineering teams, modernized Engineering practices, implemented AI-enabled development workflows, improved delivery velocity, and created a culture of accountability, quality, and continuous improvement. The VP of Engineering will be expected to be a player-coach and contribute directly to the platform when needed, including defining architecture and technical design, solving complex engineering problems, prototyping solutions, and contributing code (where needed).

Requirements

10+ years of Engineering leadership experience, including experience leading managers, technical leads, and distributed Engineering teams.
Experience as a VP of Engineering, Head of Engineering, Senior Director of Engineering, or equivalent leadership role in a SaaS, enterprise software, platform, or technology company.
Proven ability to build, restructure, scale, and lead high-performing Engineering organizations.
Experience managing distributed teams across onshore, nearshore, and/or offshore models.
Demonstrated success leading Engineering transitions, reorganizations, team migrations, location strategy changes, or major operating model transformations.
Strong full-stack technical background with the ability to understand, challenge, and contribute to frontend, backend, API, data, cloud, and infrastructure decisions.
Hands-on software development experience, with the ability and willingness to contribute directly to architecture, prototypes, technical design, code, or critical problem-solving when needed.
Strong experience modernizing SDLC practices, improving delivery velocity, and increasing Engineering predictability.
Hands-on experience implementing automation across CI/CD, testing, release management, infrastructure, observability, security, and quality gates.
Experience adopting and operationalizing AI-assisted Engineering tools and practices.
Strong technical depth across software architecture, cloud infrastructure, APIs, data, DevOps, security, scalability, and enterprise-grade software delivery.
Ability to partner effectively with Product, UX, GTM, Customer Success, Finance, HR, and executive leadership.
Excellent communication skills with the ability to clearly explain technical strategy, risks, tradeoffs, capacity, and delivery progress to executive and board-level audiences.
Strong judgment, urgency, accountability, and ability to lead through ambiguity and change.

Nice To Haves

Experience in B2B SaaS, enterprise software, marketing technology, fintech, financial services, insurance, or other regulated industries.
Experience with AI-assisted development platforms such as GitHub Copilot, Claude Code, Cursor, ChatGPT, or similar tools.
Experience building Engineering organizations that leverage contractors, nearshore development centers, or global delivery partners.
Experience leading cloud-native, API-first, data-driven, or highly configurable platforms.
Experience improving Engineering organizations that previously lacked roadmap visibility, backlog discipline, release predictability, or clear ownership models.
Experience implementing quality engineering, automated regression testing, performance testing, security scanning, and production observability at scale.
Experience working in a growth-stage company where Engineering must balance customer commitments, platform modernization, technical debt, and new product innovation.

Responsibilities

Build, lead, and scale a high-performing Engineering organization across U.S.-based, nearshore, and offshore talent.
Define the Engineering operating model, team structure, roles, ownership boundaries, and delivery expectations required to support company growth.
Recruit, develop, coach, and retain strong Engineering leaders, architects, engineers, QA professionals, DevOps resources, and technical leads.
Establish a culture of accountability, technical excellence, collaboration, urgency, and continuous improvement.
Create clear performance expectations, career paths, team health metrics, and leadership development plans.
Ensure Engineering teams are aligned to product strategy, customer commitments, business priorities, and measurable outcomes.
Lead and coordinate the relocation and transition of Engineering capabilities to the U.S., supported by nearshore contractors and/or offshore partners.
Develop and execute a comprehensive transition plan that preserves institutional knowledge, reduces operational risk, and prevents delivery disruption.
Establish structured knowledge transfer processes, documentation standards, shadowing models, codebase ownership transitions, and technical readiness checkpoints.
Coordinate hiring, onboarding, role transitions, contractor engagement, vendor management, and team ramp plans.
Identify key-person dependencies, architectural risks, delivery risks, and operational gaps, then create mitigation plans.
Partner with Product, Customer Success, Sales, Operations, Finance, HR, and executive leadership to ensure the transition is well-coordinated and clearly communicated.
Maintain delivery continuity throughout the transition while progressively improving Engineering quality, speed, and predictability.
Design and implement an AI-enabled software development lifecycle that improves Engineering productivity, quality, and speed.
Evaluate, adopt, and operationalize AI-assisted development tools for coding, test generation, documentation, code review, requirements interpretation, refactoring, technical support, and release readiness.
Create clear governance for AI usage, including security, quality, code ownership, IP protection, compliance, review standards, and acceptable use.
Build workflows that combine human technical judgment with AI acceleration across planning, design, development, testing, deployment, and post-release monitoring.
Partner with Product and UX to ensure requirements, designs, and acceptance criteria are structured in a way that enables faster and higher-quality AI-assisted development.
Establish metrics to measure the impact of AI on delivery velocity, defect rates, cycle time, developer productivity, rework, and customer outcomes.
Continuously refine the SDLC to reduce manual effort, eliminate bottlenecks, and improve flow from idea to production.
Drive consistent, predictable, high-quality software delivery across multiple teams and initiatives.
Establish delivery operating rhythms, including planning, estimation, dependency management, release readiness, sprint/release reviews, and executive reporting.
Implement automation-first Engineering practices across CI/CD, testing, QA, observability, security scanning, infrastructure provisioning, deployment, and release management.
Improve speed without compromising quality by reducing rework, strengthening requirements readiness, improving technical design, and automating repetitive work.
Define and track Engineering performance metrics such as cycle time, deployment frequency, defect escape rate, lead time, test coverage, production incidents, reliability, and team capacity.
Ensure teams have clear definitions of ready and done, strong acceptance criteria, automated quality gates, and disciplined release practices.
Create mechanisms for rapid feedback from customers, production usage, support issues, and post-release performance data.
Partner with Product and executive leadership to translate company strategy into a scalable technical strategy and execution roadmap.
Provide strong technical leadership across architecture, platform scalability, reliability, security, performance, integration strategy, and technical debt management.
Ensure Engineering investments are aligned to business outcomes, customer commitments, revenue priorities, and long-term platform health.
Make practical build-versus-buy decisions and avoid unnecessary internal tooling when proven external solutions are available.
Create architectural review practices that support speed, consistency, extensibility, and maintainability.
Balance near-term delivery needs with long-term technical sustainability.
Partner closely with Product Management, Product Design, and GTM teams to ensure Engineering is focused on the highest-value priorities.
Help improve the product development process by strengthening requirements clarity, feasibility assessment, estimation, and delivery planning.
Collaborate with Sales and Customer Success on strategic customer commitments, technical feasibility, delivery timelines, and escalation management.
Support executive and board-level communication regarding Engineering capacity, delivery progress, transition status, risks, and investment needs.
Build trust across the organization by communicating clearly, escalating early, and delivering on commitments.
Create visibility into Engineering capacity, team allocation, delivery status, risks, dependencies, and tradeoffs.
Manage Engineering budgets, hiring plans, contractor spend, vendor relationships, and resource allocation.
Identify and reduce operational, security, scalability, architectural, delivery, and personnel risks.
Establish strong incident management, production support, reliability, and postmortem practices.
Ensure Engineering processes support security, compliance, auditability, privacy, and enterprise customer expectations.
Build a culture where quality, security, and reliability are embedded into the development process rather than treated as late-stage checks.
Serve as a hands-on technical leader who can contribute directly to platform architecture, technical design, prototyping, troubleshooting, and implementation when needed.
Bring strong full-stack development experience across modern frontend, backend, API, data, cloud, and integration architectures.
Review and guide critical technical decisions, architecture proposals, code quality standards, design patterns, and engineering tradeoffs.
Act as a technical escalation point for complex platform, scalability, reliability, performance, integration, data, and security challenges.
Partner directly with engineers to unblock delivery, improve technical quality, and model strong engineering practices.
Contribute code, prototypes, proof-of-concepts, technical documentation, or architectural designs when the situation requires hands-on involvement.
Balance strategic leadership with practical technical judgment, ensuring the organization moves quickly without creating unnecessary complexity or technical debt.