Founding Backend Engineer - AI & Data

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- 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.

- A future leader. You'll help shape our engineering culture and can quickly grow into leadership as the company scales.

- 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, Node.js, PostgreSQL, high-concurrency systems.

- 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.

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.