Currently hiring
across the network.

Our Client is an AI-driven document intelligence company focused on transforming tax and accounting workflows through machine learning and automation. Recently acquired by Thomson Reuters, the company maintains a fast-paced startup culture while benefiting from strong enterprise backing.

Key Responsibilities:
- Build and scale ML deployment systems for training and production
- Design scalable backend architecture for rapid product development
- Develop pipelines that extract structured data from complex tax documents
- Integrate LLM workflows, ML inference systems, monitoring, and business logic
- Build and maintain APIs, database layers, and backend infrastructure
- Support CI/CD pipelines and engineering velocity
- Collaborate directly with accountants and end users to refine workflows and product requirements
- Own features and systems end-to-end from architecture to deployment

Required Qualifications:
- 5+ years of backend engineering experience
- Strong Python development experience
- Experience handling large and complex datasets
- Proven ownership of features from design through deployment
- Strong backend system design and architecture experience
- Comfortable working directly with customers or end users
- Ability to thrive in fast-paced product environments
- Willingness to work onsite in San Francisco or relocate

Preferred Qualifications
- Experience in Big Tech or high-scale engineering organizations

Experience with:
- GCP
- Kubernetes
- Modern backend frameworks
- Production ML systems
- LLM workflows
- Startup or scale-up experience preferred

Full-time · IT & Software · Posted 6 Jun 2026