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Clipbook is reinventing how leaders listen to and engage with information at scale. The platform ingests, comprehends, summarizes, and surfaces insights from traditional news, TV, podcasts, social media, and internet data across text, audio, and video in real time. Founded in 2023, Clipbook has grown to 200+ clients including BCG, Weber Shandwick, and government agencies. The company bootstrapped to seven-figures in ARR before raising a $3.3M seed round co-led by Mark Cuban. The founding team includes veterans from BCG, Bain, Harvard, Stanford, Oxford, the White House, and Congress, with prior startup experience backed by top-tier VCs.
You will join a small but mighty engineering team with engineers from Meta, Stripe, and AWS as a key contributor. You'll architect and build core systems, driving key decisions across the stack and owning feature development end-to-end. A major focus is integrating AI into real-world workflows—putting LLMs and ML models into production for RAG pipelines, embeddings, prompt execution, agentic systems, and fine-tuned models. You'll design systems that scale as the company grows 10x while being pragmatic about current vs. future investments. You'll develop performant APIs and services that power the product end-to-end, ensuring reliability, security, and seamless customer experience.
REQUIREMENTS:
- 3+ years building and scaling production systems
- Strong backend fundamentals (services, data models, distributed systems) with deeper expertise in one or more areas
- Genuine excitement to build quickly and ship fast
- Experience with cloud infrastructure, containerization, and CI/CD (AWS/GCP, Docker/K8s, CI/CD pipelines)
- Excellent communication skills
- Depth in one or more of: Data Engineering (Spark, Kafka, Flink, BigQuery, streaming pipelines, ETL at scale); Distributed Systems (high-volume scaling, fault tolerance, eventual consistency); AI/ML (LLMs in production, RAG, embeddings, fine-tuning, inference optimization); Backend (Python, TypeScript, PostgreSQL, high-concurrency systems)
