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DevOps Engineer

$45 - $60 per hour

Switch Intelligence Inc.

About Switch

Switch Intelligence, Inc. is an early-stage company building the platform that runs a company's commercial motion across marketing, sales, and customer operations. We are industry agnostic, and our buyers are companies between $250 million and $3 billion in revenue in manufacturing, healthcare, business services, distribution, and technology alike. Switch is based in NYC and founded by an operator who spent the last 20 years leading commercial organizations across the world's largest technology companies. 

We are looking for a strong DevOps Engineer to build the cloud, deployment, and operational foundation of the Switch Intelligence Platform — a multi-tenant, source-agnostic data streaming and intelligence system . You will stand up infrastructure as code on Google Cloud Platform , build CI/CD for application and data services, and establish secrets management, monitoring, and cost controls that a small engineering team can operate without a dedicated platform function. The platform runs on Docker and Kubernetes (GKE) and includes PostgreSQL , a Neo4j knowledge graph , event streaming, and a lakehouse layer. The ideal candidate has 5+ years of professional experience and has built production infrastructure from zero at an early-stage company. 

Hit Apply below to send your application for consideration Ensure that your CV is up to date, and that you have read the job specs first.

Engagement Structure

This is a phased contract engagement. All phases are contracted with the same named engineer at a rate fixed at signing. 

  • Phase 1 — approximately 2 to 3 weeks. Cloud account and project structure, CI/CD for the application layer, environment separation, secrets management, and an observability baseline. 
  • Phase 2 — approximately 3 to 4 weeks. Infrastructure as code for the data platform, orchestration deployment, pipeline deployment, and cost controls. 
  • Phase 3 — ongoing retainer, 8 to 16 hours per month. Maintenance, upgrades, dependency management, and incident response. 
  • Phase 4 — production ramp, timing to be confirmed. Hardening, load readiness, on-call setup, and runbook finalization. 

Key Responsibilities

  • Design and implement cloud infrastructure as code on Google Cloud Platform using Terraform, Pulumi, or equivalent, with reproducible environments rather than hand-configured resources. 
  • Build and maintain CI/CD pipelines for application services, data services, and infrastructure changes. 
  • Containerize services and deploy them to Kubernetes (GKE) , including workload configuration, autoscaling, and resource limits. 
  • Implement secrets management and access controls scoped to least privilege across environments. 
  • Establish environment separation across development, staging, and production, including data isolation between environments. 
  • Deploy and operate infrastructure for PostgreSQL Neo4j event streaming (Kafka or Google Pub/Sub), Redis , and object storage. 
  • Deploy and operate orchestration infrastructure for data pipelines using Airflow, Dagster, Prefect, or similar. 
  • Implement monitoring, logging, alerting, and tracing that surfaces production issues and suppresses noise. 
  • Implement cost controls, budget alerting, and resource tagging across GCP projects. 
  • Design and document backup, restore, and disaster recovery procedures for stateful services. 
  • Build network configuration including VPC design, private service access, ingress, and TLS termination. 
  • Produce runbooks and architecture documentation as a deliverable of each phase, and conduct a recorded handover walkthrough with the engineering team. 
  • Collaborate closely with the Data Engineering and Backend functions on deployment requirements and environment needs. 
  • Troubleshoot complex production infrastructure and deployment issues. 

Required Skills

  • 5+ years of professional DevOps, Platform, or Site Reliability Engineering experience
  • Demonstrated experience building production infrastructure from zero at an early-stage company, rather than maintaining an existing platform. 
  • Strong infrastructure as code practice with Terraform, Pulumi, or equivalent, including module design and state management. 
  • Hands-on experience with Google Cloud Platform , or equivalent depth in AWS or Azure with demonstrated ability to transfer to GCP. 
  • Production experience with Docker and Kubernetes , including managed Kubernetes services. 
  • Experience building CI/CD pipelines with GitHub Actions, Jenkins, GitLab CI, Bitbucket Pipelines, or similar. 
  • Experience deploying and operating stateful data infrastructure , including relational databases and message queues or streaming platforms. 
  • Experience with secrets management tooling such as Google Secret Manager, HashiCorp Vault, or similar. 
  • Experience with monitoring and observability tooling such as Prometheus, Grafana, Datadog, Google Cloud Operations, or similar. 
  • Working knowledge of Linux systems administration and networking fundamentals. 
  • Strong scripting ability in Python, Bash, or Go
  • Strong understanding of Git and software development workflows. 
  • Demonstrated ability to write clear technical documentation in English. 
  • Ability to independently troubleshoot and resolve complex technical problems. 

Nice to Have

  • Experience deploying and operating Neo4j or another graph database in production. 
  • Experience operating Kafka Google Pub/Sub , or similar event streaming infrastructure at production scale. 
  • Experience with multi-tenant infrastructure, including tenant isolation at the infrastructure layer. 
  • Experience deploying data orchestration frameworks such as Airflow, Dagster, or Prefect. 
  • Experience with lakehouse or warehouse infrastructure such as BigQuery, Snowflake, or Databricks. 
  • Experience with Ansible, SonarQube, Artifactory , or similar DevOps tooling. 
  • Experience implementing SOC 2 or comparable control frameworks at an early-stage company. 
  • Experience with FinOps practices and cloud cost optimization. 

Ideal Candidate

The ideal candidate is a hands-on infrastructure engineer who has done greenfield work before and knows what to build first. You should be comfortable taking an early-stage codebase with no deployment story and delivering a working pipeline, reproducible environments, and documentation another engineer can operate from. 

You should be able to reason about real architectural trade-offs — for example, when managed services are worth their cost premium against self-hosted alternatives, and where automation pays for itself at this team size versus where it does not. We value honest technical pushback grounded in correctness, operability, and cost. 

You should build proportionate to a seed-stage company . We are looking for infrastructure a small team can operate and extend, not a platform designed for an organization we do not yet have. 

Behavioral and Cultural Competencies

Predictive Rigor. We study what already happened before we make a claim about what happens next, and every forward claim traces back to evidence in the record. 

Transparency & Candor. We tell each other the truth early, including when the estimate was wrong or the news is bad, with respect for the person and without softening the substance. 

Excellence. We ship work we are willing to put our name on, and good enough is a deliberate decision with a stated cost rather than a place we end up by default. 

Disciplined Leverage. We automate, reuse, and reach for the best tooling available to move faster than our size suggests, and we never take the time back out of correctness, testing, or operability. 

Outcome Orientation. We can state plainly what changes for the customer before we build, and activity delivered is evidence that we are working rather than evidence that we are right. 

Curiosity. We stay close to customers, the market, the people we work with, and the tools available, and we ask why a system, or a business behaves the way it does before we assume. 

Compensation and Location

This is a contract engagement. The rate for the build phases is $45 to $60 per hour USD depending on experience. The rate for the ongoing retainer is $45 per hour USD . The rate is fixed at signing across all phases. This role is fully remote and we will consider candidates anywhere in the world. 

Wherever you are based, this role requires a minimum of four hours of daily working overlap with United States Eastern Time. 

Start date is immediate. 

How to Apply

Email us at with your CV, please attached a short cover note to your email. In the cover note, describe a production environment you built from zero. xhyhwjd Include what you chose, what you deliberately did not build, and what you would do differently. Include links to public work if you have it. 

Vacancy posted 6 days ago
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