Platform Engineer — Backend & Product Infrastructure

About the Company

Our client is a venture-backed applied AI company building technology for civil, structural, and MEP engineering firms.

Their thesis is blunt: most of what a practicing engineer does today is theoretically automatable, and almost none of it has been touched by AI. Their platform automates complex engineering workflows and turns customer-specific deployments into reusable products that scale across firms.

The team is small. This is one of the first engineering hires, working directly with the CTO.

About the Role

Every new firm arrives with its own systems, identities, data sources, and workflows. Your job is to turn that variety into shared software, so the fifth customer launches in days rather than the weeks the first one took. The marginal cost of the next customer is the number you own.

This is a backend engineering role that includes infrastructure. It is not an infrastructure role that occasionally touches code. The ideal candidate is a strong backend engineer who can design multi-tenant application systems, write production services, and own the cloud infrastructure those systems run on.

What You Will Build and Own

• The shared application platform behind every customer deployment
• Multi-tenant architecture with secure customer and data isolation
• Identity, authentication, authorization, and tenant-provisioning systems
• Reusable integrations against customer source systems, built from what the forward deployed engineers hit in the field
• Internal APIs and tooling that let customer-facing engineers ship faster
• Production backend code in Kotlin and Python, plus customer-facing product code when a deployment needs it
• The delivery path and the reliability of everything you build: local development, preview environments, testing, CI/CD, observability, and incident response
• Technical architecture and long-term engineering direction, alongside the CTO

What Our Client Is Looking For

• Strong backend or platform software engineering experience
• A history of writing and operating production application code, not only managing the systems it runs on
• Experience designing APIs, backend services, or distributed application systems
• Experience with multi-tenant SaaS architecture, customer isolation, identity, or access control
• The ability to look at five bespoke customer builds and find the one abstraction underneath them
• Strong cloud experience, preferably AWS
• Comfort building the first version of important systems with no existing platform team behind you
• Strong technical judgment and the ability to balance speed against long-term architecture
• Willingness to move between backend, infrastructure, internal tooling, and product engineering in the same week
• Able to work in person in New York City and travel occasionally**

This Role Is Not a Fit If

• Your background is primarily traditional DevOps, cloud administration, or production support
• Most of your work has focused on CI/CD and infrastructure configuration without significant backend development
• You want a role focused exclusively on Kubernetes, Terraform, monitoring, or release engineering
• You would rather maintain an established platform than design one from the beginning
• You do not want to contribute to product or application code
• You require clearly separated responsibilities between backend, platform, and infrastructure engineering

Technology

Backend: Kotlin and Python
Frontend: Next.js, Vercel, and Tailwind CSS
Infrastructure: Multi-tenant AWS environment

Kotlin experience is helpful, but the stronger signal is real experience building backend platforms and production services in languages such as Kotlin, Java, Go, or Python.

Compensation and Benefits

Base salary of $200,000 to $280,000, depending on experience and impact
Founding-stage equity
Full healthcare benefits
In-person New York City office

Why This Role Matters

Every new customer introduces different identity systems, integrations, data sources, and technical workflows. This role turns those differences into reusable software, letting the company support more customers without adding proportional engineering complexity. You will own the backend and platform foundation of an early-stage AI company rather than maintain someone else's infrastructure.