About Basis

Basis equips accountants with a team of AI agents to take on real workflows.

We have hit product-market fit, have more demand than we can meet, and just raised $34m to scale at a speed that meets this moment.

Built in New York City. Read more about Basis here.

About the Team

The Platform Engineering team at Basis designs, builds, and operates the infrastructure that powers our AI research and products.

We’re a lean, deeply technical group that loves architecting large-scale distributed systems from first principles.

We obsess over clarity—clean abstractions, simple mental models, and crisp interfaces that let our AI and product teams move fast without breaking things.

We’re not building “features.” We’re building capabilities for an AI accountant: scalable services, efficient data pipelines, and end-to-end observability that make the entire company move faster.

About the Role

As a Platform Engineer at Basis, you’ll own projects end-to-end—from scoping to delivery.
You’ll act as the Responsible Party (RP) for the systems you design, meaning you’re empowered to decide how to build them, how to measure success, and when they’re ready to ship.

You won’t be managed—you’ll be trusted. You’ll plan your own projects, collaborate closely with your pod, and take full accountability for execution and quality.
You’ll build systems that serve every part of Basis: AI, product, and internal agents alike—and you’ll make those systems fast, reliable, and legible.

What you’ll be doing:

1. Build and scale our core infrastructure

• Architect and scale services for reliability, cost, and growth.

• Define deployment and runtime patterns (containers, orchestration, IaC, secrets, CI/CD).

• Design observability systems (metrics, logs, traces) and make recovery paths routine.

• Own your services in production—understand their behavior and continuously improve them.

2. Design the data systems that power our AI

• Build pipelines that ingest, transform, and deliver high-quality financial data.

• Encode validation, lineage, and drift detection directly into workflows.

• Serve clean, well-modeled datasets to agents and product surfaces with clear contracts.

• Continuously simplify—turn complexity into elegant, composable systems.

3. Model the world our AI operates in

• Capture accounting entities, relationships, and invariants as data models and schemas.

• Debate and design the abstractions that make reasoning and automation possible.

• Build ontologies that encode domain rules—what agents can and cannot do.

4. Operate with ownership and clarity

• Plan and execute your projects as an RP—scoping, architecting, implementing, and delivering.

• Document decisions clearly so others can build on your work.

• Run your own postmortems and continuously improve how you build.

• Collaborate with your pod (Platform, ML, Product) to align on priorities and unblock quickly.

📍 Location: NYC, Flatiron office. In-person team.

What Success looks like in this role

• Owner: You run your projects from concept to production and hold the bar for quality.

• Engineer: Your systems are simple, scalable, observable, and elegant.

• Partner: Other teams build faster because of the clarity of your abstractions.

• First-principles thinker: You don’t just follow patterns—you understand why they exist.

• Builder: You work with conviction, communicate clearly, and raise the bar for those around you.

In accordance with New York State regulations, the salary range for this position is $100,000 –$300,000. This range represents our broad compensation philosophy and covers various responsibility and experience levels. Additionally, all employees are eligible to participate in our equity plan and benefits program. We are committed to meritocratic and competitive compensation.