Array is a financial innovation platform that helps digital brands, financial institutions, and fintechs get compelling consumer products to market faster. We deliver a suite of credit and identity monitoring tools, privacy protection, and a financial ads marketplace via embeddable widgets or a clean, modern API. Our private label offerings help drive revenue and increase engagement for our customers while empowering millions of consumers to achieve their financial goals. As a remote-first company, we’re focused on providing opportunities for high performing individuals to have deep impact in the fast growing fintech space. A clear mission, a commitment to continuous improvement and a willingness to experiment empower us individually and together deliver the best products for our clients and users.
What You'll Do
As an Infrastructure Engineer at Array, you will help us build, operate, and scale our cloud environments. You will speak GCP (Google Cloud Platform) fluently, thrive on problem solving, and be naturally curious about how systems behave. Using telemetry, logs, and metrics you will find the why, then drive clear next steps that improve reliability and scalability. You will work closely with application teams, support teams, and infrastructure partners to diagnose issues, improve platform health, and deliver solutions. You must be comfortable with ambiguity, exhibit strong ownership, and the ability to turn unclear problems into clear, actionable work. This role helps ensure our systems are scalable, reliable, and well understood, while enabling product teams to move faster with confidence.
This role reports to the Engineering Manager. All Engineering roles at Array are subject to On-Call rotations after a ramp/training period.
Key Responsibilities
Take cloud problems, investigate deeply, explain root causes clearly, and propose practical solutions
Own work end to end, drive it to completion, and communicate progress consistently
Build, operate, and improve GCP infrastructure, with some AWS support as needed
Support Kubernetes workloads on GKE and help teams run reliable, cost effective systems at scale
Work with core GCP building blocks including: Kubernetes and containerized workloads, Queueing and messaging systems such as Google Pub Sub, Amazon SQS, RabbitMQ, or similar, Relational database systems like Postgres and Microsoft SQL Server, Data and storage systems such as object storage and BigQuery, Networking components including load balancers, web application firewalls, and traffic routing
Use logs, metrics, and tracing to troubleshoot production systems and improve performance and reliability
Identify opportunities to simplify architecture, reduce operational overhead, and improve scalability
Bring curiosity and follow through to understand how cloud resources work and why they behave the way they do
Maintain a habit of using AI tools to think, build, and ship faster—it’s your default, not an afterthought.
Required Qualifications
2+ years of hands on experience operating production systems in GCP
Working knowledge of AWS or another major cloud provider
Strong fundamentals in networking, compute, storage, identity, and permissions
Kubernetes experience, especially operating workloads in production
Familiarity with scalable system components such as queues, databases, storage, and load balancing
Comfort troubleshooting live systems using telemetry and evidence, not guesswork
Ability to take ambiguous requests and turn them into clear plans and deliverables
Strong communication and cross team collaboration skills
A belief that AI is reshaping work, you instinctively use it to accelerate everything you do.
Our Stack
GCP and AWS, GKE and Kubernetes, Terraform, ArgoCD
