About the job
The Opportunity
If you've collaborated with hardware teams, you're aware of the chaos that can stem from an overlooked change request or vital context that never reaches the appropriate person. Reflow is here to bridge that gap. We are developing the first AI-enhanced platform specifically designed for hardware product development, one that listens across the tools teams are already utilizing, maintains a comprehensive view of every program, and proactively coordinates across disciplines when changes occur.
This is an incredible opportunity for a hands-on backend engineer to construct the core services and AI infrastructure that will power this platform, supported by a parent company that is at the forefront of innovation in engineering and manufacturing.
Who We're Looking For
We are in search of a backend engineer who is adept at delivering reliable, well-architected systems and takes full responsibility for the services they create. The ideal candidate has practical experience with Python, FastAPI, and PostgreSQL, and is comfortable developing everything from REST APIs to background task pipelines to AI agent infrastructures. You should be utilizing AI coding tools like Cursor, Copilot, or Claude to enhance your productivity, and be excited about creating the backend for the first AI-native platform for intricate hardware development.
This senior engineer will collaborate closely with our engineering team, AI researchers, and the head of product to build the services that convert unstructured inputs (such as call transcripts, emails, documents, and datasheets) into structured engineering artifacts (requirements, project plans, dependencies), orchestrate intelligent AI agents for proactive coordination, and deliver real-time project intelligence to users. This role is hands-on—you will be coding daily, contributing to system design decisions, and aiding in establishing backend engineering best practices as we expand.
What You'll Do
Your daily responsibilities will include:
- Designing and implementing RESTful APIs with OpenAPI specifications and auto-generated client SDKs using SQLAlchemy and PostgreSQL.
- Developing ingestion pipelines utilizing Celery and Redis that integrate with tools teams already use (file storage, messaging, email) and extract structured engineering artifacts from unstructured inputs.
- Building and enhancing agentic AI workflows using LangChain, LangGraph, and related frameworks for structured data extraction, risk detection, dependency analysis, and proactive team coordination.
- Integrating LLM APIs (such as Anthropic Claude, OpenRouter) with streaming (SSE), error management, and cost optimization.
- Deploying and managing services on Google Cloud Platform (Cloud Run, Cloud SQL, Memorystore) using Terraform.

