Vice President of Engineering, SundaySky
$260-280k
+ Annual bonus + Equity
ChatGPT
Senior and Expert level
Remote from US
Smart video platform
Open for applications
Smart video platform
101-200 employees
B2BEnterpriseContentDigital MediaVideo
Open for applications
$260-280k
+ Annual bonus + Equity
ChatGPT
Senior and Expert level
Remote from US
101-200 employees
B2BEnterpriseContentDigital MediaVideo
Company mission
To transform CX with video-powered experiences.
Role
Who you are
- Significant hands-on software engineering experience, including recent and substantive involvement in architecture, implementation, code review, and production problem-solving
- Deep architectural expertise across modern frontend and backend systems, APIs, data, cloud infrastructure, integrations, security, observability, performance, and reliability
- Demonstrated use of AI coding agents to build, test, refactor, debug, or maintain production software
- Ability to design development workflows in which AI performs implementation work under experienced human direction, review, and accountability
- Experience creating technical specifications, architectural context, coding standards, guardrails, and validation methods that enable reliable agentic development
- Evidence of personally building prototypes, production capabilities, internal developer tools, agents, or engineering automation
- Experience providing technical leadership across multiple engineers, teams, or complex initiatives, whether as an architect, distinguished engineer, technical lead, Director, or Engineering executive
- Ability to lead and develop senior engineers without becoming disconnected from implementation
- Strong judgment regarding architecture, technical debt, security, scalability, platform reliability, and build-versus-buy decisions
- Experience modernizing development practices, CI/CD, automated testing, observability, infrastructure, and release processes
- Ability to operate effectively in a growth-stage environment with ambiguity, legacy constraints, limited resources, and demanding customer commitments
- Clear, direct communication with technical and nontechnical stakeholders
- A builder’s mindset, high personal ownership, intellectual curiosity, urgency, and the desire to create something meaningfully different
- Revised preferred qualifications
- Experience as a principal engineer, distinguished engineer, chief architect, hands-on Engineering Director, startup CTO, or similarly technical leader
- Experience building AI agents, LLM-enabled applications, agent orchestration systems, evaluation frameworks, or intelligent automation
- Advanced use of tools such as Claude Code, Codex, Cursor, GitHub Copilot, or comparable agentic development platforms
- Experience designing systems that combine deterministic software, generative AI, human review, and automated evaluation
- Experience with cloud-native, API-first, multi-tenant, data-driven enterprise SaaS platforms
- Experience with media generation, browser-based rendering, personalization, content technology, marketing technology, fintech, or regulated industries
- Experience leading a blended team of U.S.-based and nearshore engineers
- Experience taking broader organizational ownership after succeeding in a senior technical or architectural role
What the job involves
- SundaySky is seeking a deeply technical, AI-native engineering leader to define our architecture, transform how software is built, and lead a focused team of highly experienced engineers. This is not a traditional, management-first Vice President of Engineering role. We are not looking for an executive who has moved away from software development or whose primary strength is managing managers
- We are looking for an exceptional architect, distinguished engineer, or hands-on Engineering Director who is ready to assume broader ownership for an Engineering organization while remaining directly involved in architecture and implementation. Our Engineering model is intentionally different. We believe a smaller team of accomplished senior engineers—equipped with well-designed AI agents, automation, and disciplined technical oversight—can outperform a much larger traditional development organization
- In this model, AI performs much of the implementation work typically assigned to junior developers, while experienced engineers provide architecture, context, judgment, review, and accountability. The successful candidate will personally help build this model. They will work in the codebase, develop reference implementations, establish architectural patterns, create AI-enabled engineering workflows, and guide engineers through complex technical decisions
- They will also lead the Engineering team, establish delivery discipline, and ensure that speed does not come at the expense of security, maintainability, reliability, or product quality. This is an opportunity for a technically exceptional and ambitious leader to take the next step in their career, shape SundaySky’s technical future, and demonstrate what an AI-native software organization can accomplish
- Own SundaySky’s application, platform, data, integration, cloud, and AI architecture
- Work directly in the codebase through prototyping, implementation, code review, debugging, refactoring, and complex problem-solving
- Translate product strategy into pragmatic technical designs and executable implementation plans
- Create reference architectures, reusable components, engineering patterns, and technical standards that accelerate development
- Make sound tradeoffs between immediate delivery, architectural quality, platform scalability, and technical debt
- Lead the modernization of legacy components while preserving platform stability and customer commitments
- Serve as the principal technical escalation point for difficult architecture, performance, security, reliability, integration, and production issues
- Design and personally implement an AI-native development model in which AI agents perform a meaningful portion of coding, testing, documentation, analysis, and maintenance
- Build the context, instructions, tools, guardrails, evaluation methods, and human-review practices required for agents to produce production-quality software
- Use AI coding tools actively and regularly—not simply as productivity add-ons, but as core components of the development lifecycle
- Develop internal agents and automated workflows for implementation, testing, code review, debugging, documentation, migration, release readiness, and production support
- Determine which work can be safely delegated to AI and where experienced engineering judgment must remain directly involved
- Establish measurable standards for the quality, security, maintainability, and productivity of AI-produced code
- Continuously evaluate emerging models, tools, frameworks, and agentic development techniques
- Lead from within the work by pairing with engineers, reviewing implementations, solving difficult problems, and modeling strong engineering practices
- Provide clear technical direction to a small, senior, highly leveraged Engineering team
- Break ambiguous product requirements into well-defined architectures, technical plans, and AI-executable units of work
- Raise the technical capabilities of the team through coaching, direct collaboration, architectural guidance, and rigorous review
- Remain close enough to the code and platform to make informed technical decisions without relying entirely on secondhand reporting
- Create an environment in which engineers have high autonomy, clear ownership, strong standards, and accountability for outcomes
- Establish a lightweight, automation-first development lifecycle optimized for speed, quality, and predictability
- Improve CI/CD, automated testing, observability, security scanning, infrastructure automation, and release management
- Define clear standards for technical readiness, code review, test coverage, release readiness, and production quality
- Use metrics such as cycle time, deployment frequency, defect escape rate, reliability, and AI-generated contribution quality to improve execution
- Partner closely with Product and Design to convert strategy and requirements into executable technical work
- Provide clear visibility into delivery status, capacity, dependencies, technical risks, and tradeoffs
- Build and lead a deliberately small team of highly experienced U.S. and nearshore engineers
- Recruit engineers who combine strong technical judgment with effective use of AI-assisted development
- Create clear ownership across applications, services, platform components, and production operations
- Manage performance directly and candidly while minimizing unnecessary organizational layers and process
- Scale the organization thoughtfully, using automation and AI leverage before defaulting to additional headcount
- Foster a culture of urgency, experimentation, craftsmanship, accountability, and continuous learning
Our take
Producing, distributing and optimising video content can be a painstaking process, especially at scale. SundaySky solves this problem by allowing videos to be created dynamically and at scale - in the same way webpages are.
SundaySky's video generating engine creates and renders videos automatically in seconds, and has created billions of video experiences to date. This solution has big appeal for enterprises, and SundaySky now serves big-name customers such as Comcast, Dell and United Airlines.
SundaySky's main challenge is competing with companies that offer similar services, such as Loom and Ziflow. However, the company's impressive client roster and the speed of its engine are strong indicators of future success. It also continues to add new features, for example, a generative AI assistant that facilitates faster user-driven video creation through conversational text prompts.
Steph
Company Specialist at Welcome to the Jungle
Insights
Top investors
12% employee growth in 12 months
Company
Funding (last 2 of 6 rounds)
Jun 2020
$8.9m
LATE VC
Aug 2017
$7m
SERIES D
Total funding: $84m
Company HQ
Tel Aviv-Yafo, Tel Aviv District
Leadership
Drake Pruitt
(CEO & Board Member)Operating Partner for Product and AI Innovation at Clearhaven Partners. Previously spent 5 years at Amazon Web Services, ultimately as PE Product Innovation Lead. Was also VP at Anaconda and President, CEO and Board member at OPENFORCE.
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