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Forward Deployed Engineer, Infra

Engineering · Posted 3 months ago

We are looking for an Infrastructure Engineer with 2–5+ years of experience to own end-to-end deployment of Reducto into enterprise customer environments – from VPC to bare metal on-prem. You'll be the engineer who makes complex deployments work, partnering directly with customer IT, security, and platform teams. This...

Way of working
On site
Location
San Francisco, CA
Pay range
$200,000 to $300,000
Level
Mid
Experience
3+ years
Type
Full time
Visa sponsorship
Not offered for this role
The company
AI/ML · 50 to 200 people

Skills that matter here

PythonKubernetesHelmTerraformAWSGCPAzureDockerGPU InfrastructureReplicated/KOTSLinuxNetworkingCloud IAM

The full description

We are looking for an Infrastructure Engineer with 2–5+ years of experience to own end-to-end deployment of Reducto into enterprise customer environments – from VPC to bare metal on-prem. You'll be the engineer who makes complex deployments work, partnering directly with customer IT, security, and platform teams. This role requires strong technical chops in Kubernetes, networking, and cloud infrastructure, combined with excellent communication skills – you'll be in live channels and on calls with customer engineers and senior leaders. We have a team lead already in place and are looking for both a mid-career engineer and a more junior hire to scale the team.

What you will be doing

- Leading end-to-end deployment of Reducto into customer environments – planning, configuration, testing, and rollout across VPC and on-prem setups

- Working directly with enterprise customer teams (e.g., Harvey) – sometimes visiting their offices, communicating in shared channels with their engineers and senior leaders

- Debugging and resolving customer-specific infrastructure issues like K8s misconfigurations, cloud IAM edge cases, and networking problems

- Building monitoring, telemetry, and automation – turning one-off customer work into repeatable deployment patterns that scale across future deployments

- Understanding the hardware powering Reducto's ML models to successfully deploy them onto customer-controlled infrastructure

How hiring runs

  1. 1Hiring Manager Screen
  2. 2Phone Screen
  3. 3Full-Day Onsite

Interested in this one?

There is no apply button here on purpose. Tell us about yourself, we book a short call, and if this role fits we walk you through the company and ask before anything is sent. Always free for you.

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