ABOUT CIRCUIT

Circuit is building the world’s first company-centric knowledge network. Our AI-powered platform turns fragmented information into actionable knowledge that can be securely shared across partners, vendors, and customers. Backed by a senior team and early enterprise traction, we’re moving fast, and we’re looking for a sharp and hungry Senior Python Backend Engineer to help build our ML services.

EXPERIENCE

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• Strong Python and async experience

• Experience with AI/ML APIs (OpenAI, Anthropic, etc.)
• Building SDKs / internal libraries
• Knowledge of RAG/agentic architectures (bonus)
• Experience running web services at scale (FastAPI, Flask, or Django)
• Experience with batch processing systems (Airflow, Argo Workflows, Dagster)
• Experience with performance and memory optimization
• Experience with Go, Kubernetes, Datadog is a plus

HUMAN SKILLS

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• Strong problem-solving abilities and adaptability in a fast-paced, dynamic environment

• Results oriented and ability to move fast, while still maintaining quality
• Team-first mindset, low ego and collaborative
• Strong desire to win
• Eager to experiment with emerging AI tools and practices, constantly seeking better, smarter ways to operate.

ROLE SUMMARY

This backend engineering role is focused on supporting and building out our ML services, as well as our ML infrastructure and tooling. Our ML infrastructure and services are built in Python, and our overall backend infrastructure is built in Go. You’ll be expected to be the Python expert, with a deep understanding of how to build resilient and high quality services in Python, as well as how to support a team that is moving fast to build out new features. You will work closely with our ML team, helping with feature buildouts and execution, and with the rest of our backend team, aligning on best operational practices.

KEY RESPONSIBILITIES

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• Build and maintain Python services and internal tooling that power our AI products.

• Develop frameworks and APIs that make it faster and easier for our AI engineers to experiment and ship features.
• Own the “glue” that connects AI models, data pipelines, and product experiences — so our AI engineers can focus on model quality, not boilerplate.
• Collaborate closely with AI engineers to understand pain points and automate repetitive tasks in their workflows.