Lead Cloud Engineer

The Opportunity

Carriers make pricing and product decisions on data they have to be able to trust, and all of it rides on infrastructure someone has to own outright. That is this role. You will own the cloud environments, data stores, networks, and deployment pipelines behind the Insuraviews platform, reporting directly to the CTO.

The work is senior and hands‑on. You will architect and build our cloud footprint across GCP (Google Cloud Platform), AWS (Amazon Web Services), and/or Azure, manage it as code in Terraform, administer the PostgreSQL databases the platform runs on, and build the CI/CD (continuous integration and continuous delivery) pipelines the engineering team ships through. You will own monitoring, incident response, and disaster recovery — the parts of the job where being right matters to customers in a regulated industry. You will also design the infrastructure that supports AI (artificial intelligence) and machine learning workloads on the platform, and use AI-assisted tooling in your own work where it makes what you ship better.

What we are looking for

Someone who would rather own systems end to end than hold a slice of them, and who wants to be on point when something breaks. You will set cloud and infrastructure standards for the engineering organization, document the tradeoffs behind them, and mentor developers and data engineers on cloud and infrastructure-as-code practices. As the platform and team grow, you may help define, hire for, and lead a small cloud and platform team.

Responsibilities

• Own the design, build-out, and ongoing evolution of Insuraviews' cloud environments across GCP, AWS, and/or Azure, keeping infrastructure secure, scalable, and cost-effective.
• Manage all infrastructure as code in Terraform, and architect the containerized workloads, networking, and access model the platform runs on.
• Administer, tune, and secure the platform's PostgreSQL databases, including backups, replication, failover, version upgrades, and query performance.
• Own database access controls, retention policies, and tested disaster recovery procedures, partnering with the Data Engineer on schemas and warehousing.
• Build the monitoring, logging, and alerting that catches issues before customers feel them, and lead infrastructure incident response end to end.
• Own cloud security practices, identity and access management, secrets, encryption, and vulnerability remediation, along with the evidence carrier customers ask for in security reviews.
• Build and maintain the CI/CD pipelines the engineering team ships through, with automated testing, environment promotion, and reliable rollback.
• Provide self-service tooling and documentation, and automate the operational tasks that would otherwise cost the team manual effort.
• Set and document cloud and infrastructure standards for the engineering organization, and mentor developers and data engineers on cloud and infrastructure-as-code practices.
• As the platform and team grow, help define, hire for, and potentially lead a small cloud and platform team.
• Design and operate the cloud infrastructure that supports AI and machine learning workloads on the platform, including compute, storage, and access patterns.
• Use AI-assisted tooling in your own workflow, and evaluate emerging cloud and AI capabilities where they advance reliability, capability, or cost efficiency.

Qualifications

• 5+ years in cloud engineering, infrastructure, DevOps, or site reliability engineering, with at least 2 years in a lead or senior-level role
• Hands-on production experience with at least one major cloud platform (GCP, AWS, or Azure) and working familiarity with a second
• Strong proficiency with Terraform and infrastructure as code, and experience building and maintaining CI/CD pipelines
• Experience administering production relational databases (PostgreSQL), including backup and recovery, replication, and performance tuning
• Practical experience with containers and container orchestration (e.g., Docker, Kubernetes, ECS, Cloud Run)
• Solid cloud networking and security fundamentals — VPC design, subnetting, routing, load balancing, DNS, firewall rules, and identity and access management
• Comfort using AI tools in day-to-day work, plus experience provisioning cloud infrastructure for AI or machine learning workloads, or the ability to come up to speed on it quickly
• Systematic problem-solving and debugging skills, with clear communication and the ability to collaborate across teams
• Bachelor's degree in computer science, Engineering, or a related field. Relevant experience will be considered in lieu of a degree