Founding Senior Software Engineer

About Clipbook

Clipbook aims to transform how leaders listen to and interact with the daily influx of information. Our platform processes and interprets data from sources like news, TV, podcasts, social media, and the internet in real time, across multiple formats including text, audio, and video.

Since our 2023 launch, we've expanded to serve over 200 clients such as BCG, Weber Shandwick, and multiple government entities. We achieved seven-figure annual recurring revenue through bootstrapping before securing a $3.3 million seed investment from prominent investors, including Mark Cuban.

Our founding team comprises individuals with experience at BCG, Bain, Harvard, Stanford, Oxford, the White House, and Congress, as well as founders of startups funded by Sequoia, Tiger Global, Insight Partners, Coatue, and NFX.

Role Overview

As a critical member of Clipbook's compact engineering team, which includes engineers from Meta, Stripe, and AWS, you will have considerable responsibility developing new features and ensuring rapid delivery to our broad customer base.

Key Responsibilities

• Design and develop core system architectures, lead major technical decisions, and take full ownership of feature implementation.
• Embed AI technologies into practical workflows, deploying large language models and machine learning components such as RAG pipelines, embeddings, prompt execution, agentic systems, and fine-tuned models.
• Engineer systems scalable enough to support tenfold growth, while judiciously balancing immediate and future development priorities.
• Build high-performance APIs and internal services to power the product end-to-end, focusing on reliability, security, and customer experience.

Candidate Expectations

• Possess over three years of experience designing and scaling production systems, showcasing strong backend fundamentals like services, data modeling, and distributed systems with focus areas for deeper specialization.
• Demonstrate enthusiasm for rapid development cycles and user-focused iteration.
• Have proficiency with cloud platforms and infrastructure, containerization (Docker, Kubernetes), and continuous integration and deployment pipelines, particularly on AWS or GCP.
• Exhibit excellent communication capabilities.

Technical Expertise Areas (Expertise Required in One or More)

• Data Engineering: Skilled with Spark, Kafka, Flink, BigQuery, and constructing scalable streaming ETL pipelines.
• Distributed Systems: Knowledge of designing for high-volume scaling, fault tolerance, and eventual consistency.
• AI/ML: Experience deploying LLMs in production environments, including RAG methodology, embeddings, fine-tuning, and optimizing inference.
• Backend Development: Proficiency in Python, TypeScript, PostgreSQL, and high-concurrency applications.