Founding Full-Stack Software Engineer

Clipbook•New York City, NY

2d•Remote

About The Position

Clipbook builds AI-powered media monitoring and analytics tools for communications, PR, and public affairs teams. We help them track, search, and make sense of coverage across text, audio, and video. We launched in 2023 and have grown to 200+ clients including BCG, Weber Shandwick, and dozens of government agencies. We bootstrapped to seven-figures in ARR before raising a $3.3M seed round (co-led by Mark Cuban). We plan to raise our Series A this year and we are aiming for eight-figures revenue by end of year. Our founding team has backgrounds at BCG, Bain, Harvard, Stanford, Oxford, the White House, and Congress, and has previously built startups backed by Sequoia, Tiger Global, Insight Partners, Coatue, and NFX. The Role You'd be one of the first engineers at Clipbook — joining a small but mighty engineering team with engineers from Meta, Stripe, and AWS. You'll have real influence over architecture and technical direction, and what you build will ship to 200+ customers quickly. What You'll Do Architect & build across the stack. Make architectural decisions and implement solutions across the stack (Next.js, TypeScript, React, Python, Node, SQL/NoSQL). You have the conviction to quickly build from concept to deployment to seeing clients love our product. Collaborate with customers. Work directly with users to understand pain points, join calls, hear what's working and what isn't, and rapidly iterate to deliver solutions that matter. Tackle a wide breadth of engineering challenges. Our work spans AI, data engineering, backend, frontend, and more — so there's plenty of opportunity to find projects that match your strengths and interests. Some examples include: AI/ML Integration: Productionize LLMs and classical ML models for real-world, high-uptime applications — including prompt execution, embeddings, RAG pipelines, and agentic systems. Leverage the latest in generative AI tooling and frameworks. Data Engineering: Build pipelines and infrastructure for ingesting, normalizing, and querying massive, multi-modal datasets (text, audio, video). Shape Clipbook's engineering culture. As one of the first engineers, you'll influence everything — code quality, system design principles, documentation standards, testing, deployment, and how we build as a team. You'll mentor future hires and drive best practices. We believe leaders stay hands-on: even as we grow, everyone (including managers) continues to ship.

Requirements

2–10+ years of relevant engineering experience at tech and product-driven companies.
Taken systems from zero to production and owned the full lifecycle.
Proficiency with web technologies (Next.js, JavaScript/TypeScript, React, etc.)
Genuine excitement to build quickly & ship fast.
Deep knowledge and practical experience with cloud-based services, containerization, and API development.
Experience optimizing data architectures for performance and cost.
Take ownership. When something is broken or unclear, you fix it or flag it without waiting to be asked.
Comfortable with ambiguity. You make reasonable calls with incomplete information, communicate them clearly, and adjust as you learn more.
Strong product sense and bias for action.
A future leader. You'll help shape our engineering culture and can quickly grow into engineering leadership as the company scales.

Nice To Haves

LLM fine-tuning, RAG, RLHF, or eval pipelines
Computer vision or multimodal model experience (audio, video, image)
Semantic search, vector databases, or meaning-aware retrieval
Familiarity with web scraping frameworks (Playwright, Puppeteer) and different types of API integrations (REST, GraphQL)
Comfort with asynchronous workflows, rate-limiting, and distributed systems
Startup founder or early-stage experience is a huge plus.

Responsibilities

Architect & build across the stack.
Make architectural decisions and implement solutions across the stack (Next.js, TypeScript, React, Python, Node, SQL/NoSQL).
Collaborate with customers.
Work directly with users to understand pain points, join calls, hear what's working and what isn't, and rapidly iterate to deliver solutions that matter.
Tackle a wide breadth of engineering challenges.
Productionize LLMs and classical ML models for real-world, high-uptime applications — including prompt execution, embeddings, RAG pipelines, and agentic systems.
Leverage the latest in generative AI tooling and frameworks.
Build pipelines and infrastructure for ingesting, normalizing, and querying massive, multi-modal datasets (text, audio, video).
Shape Clipbook's engineering culture.
Influence code quality, system design principles, documentation standards, testing, deployment, and how we build as a team.
Mentor future hires and drive best practices.