An early-stage AI team building production-grade extraction from unstructured documents.

Solutions Engineer

San FranciscoOn-site$125K - $155K3 - 7 years
Your mornings begin in a customer war room, tracing a Python pipeline through Kubernetes logs to figure out why a specific PDF ledger broke the parsing model. By afternoon, you are translating those edge cases into a Terraform configuration, spinning up infrastructure across AWS and GCP to deploy a hardened fix before jumping on a call to walk the client through the resolution. You will operate at the fragile, fascinating seam between raw unstructured data and production reliability, ensuring that enterprise deployments actually function in the real world. This is forward-deployed engineering where the rubber meets the road.

What they're looking for

  • 3 to 7 years of experience in solutions engineering, forward-deployed engineering, or a comparable client-facing technical role
  • Fluency writing Python and deploying containerized applications with Docker and Kubernetes
  • Working knowledge of infrastructure-as-code, specifically Terraform, across major cloud providers like AWS, GCP, or Azure
  • Comfort navigating the ambiguity of early-stage company building and directly managing enterprise client relationships
  • Familiarity with modern data stacks, including Snowflake, is a strong plus

Tech stack

PythonKubernetesAWSGCPAzureDockerTerraformSnowflake

Apply for this role

This role is one we're recruiting for on behalf of a client company; the client's identity is kept confidential at this stage. A Fluency recruiter will follow up with details.