DevOps Engineer

About the Company
Switch Intelligence, Inc. is an early-stage company developing a platform that supports commercial operations across marketing, sales, and customer operations. Its platform serves businesses with annual revenues between $250 million and $3 billion across industries including manufacturing, healthcare, business services, distribution, and technology.
Based in New York City, Switch was founded by an operator with 20 years of experience leading commercial organizations at major technology companies.
About the Role
Switch Intelligence is seeking an experienced DevOps Engineer to build the cloud infrastructure, deployment processes, and operational foundation for its multi-tenant Switch Intelligence Platform. This is a hands-on contract engagement focused on establishing production infrastructure from the ground up, rather than maintaining an existing platform.
You will build infrastructure as code on Google Cloud Platform (GCP), establish CI/CD pipelines, deploy containerized services to Kubernetes, and implement monitoring, security controls, and cloud cost management. The platform includes PostgreSQL, Neo4j, event streaming, and a lakehouse layer, requiring close collaboration with the Data Engineering and Backend teams.
The engagement is structured in phases, beginning with core cloud infrastructure and application deployment, followed by data platform infrastructure, ongoing maintenance, and a later production-readiness phase. The successful candidate will be comfortable making practical architectural decisions that balance reliability, maintainability, automation, and cost for a small engineering team.
Key Responsibilities
Design and implement reproducible cloud infrastructure using Terraform, Pulumi, or equivalent infrastructure-as-code tools.
Build and maintain CI/CD pipelines for application services, data services, and infrastructure changes.
Containerize applications and deploy services to Kubernetes using Google Kubernetes Engine (GKE), including workload configuration, autoscaling, and resource limits.
Implement secrets management and least-privilege access controls across environments.
Establish separate development, staging, and production environments, including appropriate data isolation.
Deploy and operate infrastructure for PostgreSQL, Neo4j, Kafka or Google Pub/Sub, Redis, and object storage.
Deploy and manage data pipeline orchestration infrastructure using Airflow, Dagster, Prefect, or similar tools.
Implement monitoring, logging, alerting, and tracing to identify production issues while minimizing unnecessary alerts.
Establish cloud cost controls, budget alerts, and resource tagging across GCP projects.
Design and document backup, restoration, and disaster recovery procedures for stateful services.
Configure networking, including VPC design, private service access, ingress, and TLS termination.
Produce architecture documentation and operational runbooks for each phase, including a recorded handover walkthrough with the engineering team.
Work closely with Data Engineering and Backend teams to understand deployment requirements and environment needs.
Troubleshoot complex production infrastructure and deployment issues.
Required Qualifications
5+ years of professional experience in DevOps, Platform Engineering, or Site Reliability Engineering.
Demonstrated experience building production infrastructure from scratch at an early-stage company.
Strong infrastructure-as-code skills using Terraform, Pulumi, or equivalent tools, including module design and state management.
Hands-on Google Cloud Platform experience, or equivalent depth in AWS or Azure with the ability to transfer those skills 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 tools.
Experience deploying and operating stateful data infrastructure, including relational databases and message queues or streaming platforms.
Experience with secrets management tools such as Google Secret Manager, HashiCorp Vault, or equivalent solutions.
Experience with monitoring and observability tools such as Prometheus, Grafana, Datadog, or Google Cloud Operations.
Working knowledge of Linux system administration and networking fundamentals.
Strong scripting skills in Python, Bash, or Go.
A solid understanding of Git and software development workflows.
Ability to write clear technical documentation in English and independently resolve complex technical problems.
Preferred Qualifications
Production experience with Neo4j or another graph database.
Experience operating Kafka, Google Pub/Sub, or similar event-streaming infrastructure at production scale.
Experience with multi-tenant infrastructure and tenant isolation at the infrastructure level.
Familiarity with data orchestration frameworks such as Airflow, Dagster, or Prefect.
Experience with lakehouse or data warehouse technologies such as BigQuery, Snowflake, or Databricks.
Familiarity with Ansible, SonarQube, Artifactory, or similar DevOps tools.
Experience implementing SOC 2 or comparable control frameworks at an early-stage company.
Knowledge of FinOps practices and cloud cost optimization.
Ideal Candidate
The ideal candidate is a hands-on infrastructure engineer who understands how to build a production environment from the ground up and determine which components are essential at an early stage. You should be able to deliver working deployment pipelines, reproducible environments, and documentation that another engineer can use independently.
You should also be comfortable evaluating architectural trade-offs, including managed services versus self-hosted alternatives, and deciding where automation provides meaningful value. Switch values direct communication, evidence-based decisions, technical correctness, cost awareness, and infrastructure that a small team can realistically operate and maintain.
Compensation and Engagement Structure
This is a phased contract engagement, with the same named engineer contracted across all phases at a rate fixed at signing.
Phase 1: Approximately 2–3 weeks for cloud account and project structure, application CI/CD, environment separation, secrets management, and baseline observability.
Phase 2: Approximately 3–4 weeks for data platform infrastructure as code, orchestration deployment, pipeline deployment, and cost controls.
Phase 3: Ongoing retainer of 8–16 hours per month for maintenance, upgrades, dependency management, and incident response.
Phase 4: Production ramp, with timing to be confirmed, covering hardening, load readiness, on-call setup, and runbook finalization.
The build phases pay $45–$60 USD per hour, depending on experience. The ongoing retainer pays $45 USD per hour. The rate is fixed at signing across all phases.
Location and Working Hours
This is a fully remote position open to candidates worldwide. Candidates must have at least four hours of daily working-time overlap with United States Eastern Time. The start date is immediate.
How to Apply
Email your CV to jobs@goswitch.io with a short cover note describing a production environment you built from scratch. Explain the technologies and approaches you selected, what you deliberately chose not to build, and what you would do differently in hindsight. Include links to publicly available work, if applicable.

Work arrangement
Yes