Clipbook - Founding Backend Engineer – AI & Data
Requirements
• 2–10+ years building and scaling production backend systems. You've taken systems from zero to production and owned the full lifecycle. Strong across backend fundamentals (services, data models, distributed systems), with deeper expertise in one or more areas — and a desire to keep expanding your breadth over time. • 2–10+ years building and scaling production backend systems. • Genuine excitement to build quickly & ship fast. We care about getting things into users' hands and iterating from there. • Genuine excitement to build quickly & ship fast. • You take ownership. When something is broken or unclear, you fix it or flag it without waiting to be asked. • You take ownership. • Comfortable with ambiguity. You make reasonable calls with incomplete information, communicate them clearly, and adjust as you learn more. • Comfortable with ambiguity. • Strong experience with cloud infrastructure, containerization, and CI/CD. We're building systems that will one day serve Fortune 500 executives in real-time — so reliability matters. Familiarity with AWS/GCP, containerization (Docker/K8s), and CI/CD pipelines ensures we can deliver high uptime and iterate quickly. • Strong experience with cloud infrastructure, containerization, and CI/CD. • A future leader. You'll help shape our engineering culture and can quickly grow into leadership as the company scales. • A future leader. • Technical Areas Where Depth Matters (one or more) • Data Engineering: Spark, Kafka, Flink, BigQuery, streaming pipelines, ETL at scale. • Data Engineering: • Distributed Systems: High-volume scaling, fault tolerance, eventual consistency. • Distributed Systems: • AI/ML: LLMs in production, RAG, embeddings, fine-tuning, inference optimization. • AI/ML: • Backend: Python, Node.js, PostgreSQL, high-concurrency systems. • Backend: • Nice-to-Haves • Nice-to-Haves • Computer vision or multimodal model experience (audio, video, image). This is central to our product, so it's a meaningful differentiator. • Semantic search, vector databases, or meaning-aware retrieval. • LLM fine-tuning, RLHF, or eval pipelines. • Web scraping and API integrations at scale. • Startup founder or early-stage experience is a huge plus. • What This Role Is Not • We're hiring for the application and data layer. This probably isn't the right fit if your background is primarily in firmware, embedded systems, hardware engineering, networking, or infrastructure/DevOps. • A Few Things Worth Knowing • We care more about what you ship than when or where you work, but this is an early-stage company growing fast. The pace reflects that. Our culture is intense and driven by H&H (hunger and hustle). • As one of the first engineers, you'll wear a lot of hats. There's no platform team to hand things off to yet.
Responsibilities
• Architect & build core backend systems. Drive architectural decisions across our backend stack (Python, Node.js, PostgreSQL). Own features from concept → deployment → observing users rely on what you built. We're still laying critical foundations, so we value a pragmatic, "strong opinions, weakly held" mindset — especially when decisions are expensive to unwind later. • Architect & build core backend systems. • Design scalable data infrastructure. Build and maintain pipelines for ingesting, normalizing, deduplicating, indexing, and querying massive, multi-modal datasets (text, audio, video) across news, social media, policy, and more. A lot of this is normalization, deduplication, and edge case handling. • Design scalable data infrastructure. • Integrate AI into real-world workflows. Put LLMs and ML models into production for real workflows: RAG pipelines, embeddings, prompt execution, agentic systems, fine-tuned models. Production means reliable, monitored, and cost-conscious. • Integrate AI into real-world workflows. • Design systems that scale. Build systems that will hold up as we grow 10x, while being practical about what to invest in now vs. what can wait. • Design systems that scale. • Develop performant APIs and services. Create robust interfaces and internal services that power our product end-to-end, ensuring reliability, security, and a seamless experience for customers. • Develop performant APIs and services. • Collaborate closely with users. Join customer calls, hear what's working and what isn't, and build in response. Rapidly iterate to deliver solutions that genuinely move the needle for comms/public affairs teams. • Collaborate closely with users. • Shape Clipbook's engineering culture. As one of the first engineers, you'll influence everything — code quality, system design principles, documentation standards, and how we build as a team. We believe leaders stay hands-on: even as we grow, everyone (including managers) continues to ship. • Shape Clipbook's engineering culture.
Benefits
• Equity: Early-stage grant with significant upside • Equity: • Benefits: Medical, dental, vision, 401(k), unlimited PTO • Growth: A clear path to engineering leadership as we scale • Growth:
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