Location: San Francisco, CA
Work Model: Hybrid
Industry: Enterprise AI and data infrastructure
Compensation: $200K base, $300K OTE
About the Company
Our partner is a venture-backed enterprise AI company that helps large organizations build data pipelines and modernize their data infrastructure. They combine AI agents with an in-house team of data engineers to deliver in months what traditional providers quote in years. In roughly a year and a half they have signed more than 15 enterprise customers and generated several million dollars in revenue. The team is about 35 people, led by experienced repeat entrepreneurs, with a thoughtful culture that values getting things right.
The Opportunity
This is the first forward deployed engineer based in the United States, and a founding member of the US field engineering team. You will be the engineer in the room with the customer, working with client leaders and their engineering teams to understand requirements, resolve data questions and build the pipelines using the company's agentic tooling.
Because the role sits between customers and the platform team, you will directly influence how the tooling evolves. Much of the engineering team is based overseas, so the working day starts early to allow for overlap. Weekend work is not expected outside of rare sprints, and the role is hybrid with limited travel.
Responsibilities
- Build enterprise data pipelines using the company's AI agent tooling
- Act as the technical point of contact for client stakeholders from engineers to senior leadership
- Clarify requirements, resolve data discrepancies and map data models across systems
- Work with the platform team to improve internal tooling based on field experience
- Deliver proof-of-concept projects that lead to larger engagements
- Help establish practices for the US field engineering team
Requirements
- 5-6 years of experience, with a mix of large technology company and startup experience
- Data engineering experience building enterprise data pipelines
- Strong communication skills and comfort working with senior client stakeholders
- Attention to detail and a record of reliability
- Ability to start the working day early to collaborate with an overseas engineering team
- Experience with data lake architecture or AI agent tooling is preferred