Tech Lead - Platform

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.

The Platform Engineering team at Basis builds and runs the infrastructure that powers our AI research and products. We're a lean team that loves building large-scale distributed systems from scratch. We focus on clarity: clean abstractions, simple mental models, and clear interfaces that help our product and research teams move fast.

We build the foundational capabilities an AI accountant needs. That means modeling the accounting world (concepts, workflows, constraints) and providing solid foundations: scalable services, efficient data pipelines, and comprehensive observability.

As a Tech Lead on the Platform team, you'll own the technical vision for a core part of Basis's infrastructure: how we deploy, model, and serve the data and systems our AI depends on.

You'll design solid architectures, make trade-offs clear, and teach others how to think about distributed systems effectively. You'll ensure consistency across runtime, data, and schema layers so our systems scale predictably and stay understandable as we grow.

You'll lead by example through your code, design reviews, and documented decisions, making sure the platform is both powerful and elegantly simple.

Architect and evolve our infrastructure foundations

• Design scalable, cost-efficient services across compute, storage, and networking.

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

• Build systems for observability and reliability: metrics, logs, traces, SLOs, and recovery patterns.

• Lead postmortems, define error budgets, and make operational excellence a standard practice.

Build and standardize our data platform

• Design data pipelines that ingest, validate, and transform accounting data into clean, reliable datasets.

• Define schemas and data contracts that balance flexibility with correctness.

• Build validation, lineage tracking, and drift detection into every pipeline.

• Create interfaces that make data discoverable, computable, and observable throughout the system.

Model the domain as a system

• Translate accounting concepts into well-structured ontologies: entities, relationships, and rules.

• Create abstractions that help AI systems reason safely about real-world constraints.

• Design for clarity: make complex workflows understandable through schema, code, and documentation.

Lead through clarity and technical excellence

• Own the architectural vision for your area and keep it consistent over time.

• Run effective design reviews that challenge assumptions and drive alignment.

• Mentor engineers on how to think about systems: from load testing to schema design to observability patterns.

• Simplify aggressively by removing unnecessary complexity and maintaining clean, stable abstractions.

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

• The systems you design scale cleanly and are easy for others to understand.

• Platform, ML, and product systems fit together through clear contracts and conventions.

• Your design reviews, docs, and code improve how others think about architecture.

• You make reliability measurable and downtime rare and uneventful.

• You approach every decision with clarity, conviction, and calm.