Senior Platform Engineer

As a Senior Platform Engineer at Basis Theory, you will own the infrastructure that our tokenization platform runs on: multi-region AWS compute, data, and edge. You will also own the developer platform that lets a small engineering team ship to it safely, many times a day, inside a PCI Level 1 boundary.

In this role, you'll treat infrastructure as a product: the customers are the engineers who deploy on it. You'll leverage AI tooling and deep technical expertise to eliminate toil, make sound architectural decisions, and build paved paths that make the secure, compliant way to ship also the easiest way to ship.

What you'll be responsible for:

Own and evolve our AWS footprint as code, using Terraform across multiple accounts and five regions covering ECS, Lambda, EKS, RDS, DynamoDB, Kinesis, VPC and peering, KMS, and Secrets Manager.
Build and operate the shared compute platform that every service relies on across ECS, Lambda, and EKS, including Argo CD–driven GitOps delivery and core Kubernetes add-ons for secrets, certificates, DNS, ingress, and autoscaling.
Own the edge: Cloudflare load balancing and failover pools, WAF and rate-limit rulesets, custom hostnames, and Workers, including the routing that keeps EU traffic in the EU.
Design and improve the paved path for deployment: CI/CD in GitHub Actions, promotion across environments, and the templates and tooling that make a new service production-ready on day one.
Contribute to the product codebase on cross-cutting and foundational concerns such as observability, scalability, and architecture evolution, not just infrastructure tooling.
Drive platform architecture decisions, balancing cost, blast radius, compliance constraints, and developer experience.
Own the reliability of what you build: infrastructure-level monitors and alerting as code in Datadog, multi-region failover paths, and capacity and performance work informed by our load-testing suites.
Build infrastructure inside a PCI Level 1 environment where tenant isolation, key management, and auditability are design constraints, not afterthoughts, and automate the evidence rather than assembling it by hand.
Leverage AI coding tools to accelerate infrastructure work, review, and migrations, and push the boundaries of what a small platform team can operate.
Collaborate with product engineers through pairing, design reviews, and technical guidance, raising the bar for how the whole team builds and deploys.

You may be a good fit if:

You think of infrastructure as a product with users, and you measure yourself by whether other engineers can ship confidently without you.
You have deep production experience with Terraform and AWS, along with informed opinions about how cloud infrastructure and Terraform code should be structured.
You're at home in the product codebase, not just the infrastructure repos. When a foundational problem lives inside a service, you go fix it there.
You care about the details: reproducible environments, sane module boundaries, fast and trustworthy pipelines, clear failure modes.
You are relentless about eliminating toil. When you do something manually twice, you automate the third time.
You leverage tools like Claude, GPT, or similar to accelerate your engineering work and are curious about how AI changes what a small infrastructure team can operate.
You thrive in a collaborative, low-ceremony environment where engineers own outcomes, not just tasks.
You have a proactive, problem-solving mindset. You find issues before they find customers.
You're a lifelong learner who's energized by working at the intersection of payments, security, and developer tools.

Other experiences that may help:

Operating infrastructure for high-velocity transactional systems (peaks well over 10k requests per second).
Multi-region and active/passive or active/active architectures, including failover design and DR exercises.
Building or operating platforms under PCI DSS, SOC 2, or comparable regulatory constraints.
Cloudflare or comparable edge platforms: WAF, load balancing, and edge compute.
Cost engineering and capacity planning for cloud infrastructure at scale.
Load testing and performance engineering (k6 or similar) against production-like environments.

Skillsets:

Required

Production experience owning cloud infrastructure as code, ideally Terraform on AWS
Hands-on production experience across AWS compute and data services, such as ECS, Lambda, EKS, and managed data stores
Proficiency writing and maintaining production software in Node.js, C#, Go, or a comparable language
CI/CD pipeline design and ownership (GitHub Actions, Azure DevOps, or similar)
Working knowledge of cloud networking, secrets management, and identity (IAM, OIDC)
Experience using AI coding assistants and LLM-based tools to accelerate engineering workflows

Desired

GitOps delivery with Argo CD, Flux, or equivalent
Observability practice with Datadog or comparable, with monitors, dashboards, and SLOs defined as code
Experience with edge/CDN platforms such as Cloudflare
Database operations experience (SQL Server, PostgreSQL, DocumentDB, or DynamoDB) including replication and migrations
Familiarity with compliance automation and control evidence in a regulated environment

Experience

5+ years of experience in software or infrastructure engineering, building and operating cloud platforms in production. Bonus if that experience is in payments, fintech, or compliance-heavy environments.

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