Member of Technical Staff - Backend Engineer - Data Systems and APIs

MEMBER OF TECHNICAL STAFF - BACKEND ENGINEER - DATA SYSTEMS AND APIS

About Vinci

We’re building a copilot for hardware. Software engineers have powerful AI tools. Hardware engineers still rely on workflows that take hours or days to simulate and iterate. Vinci is changing that.

Our platform combines AI, geometry processing, and physics simulation to help engineers validate designs dramatically faster than traditional tools. The system integrates foundation models with simulation engines to produce full-fidelity physical predictions in seconds instead of hours.

We’re a small team building infrastructure that connects AI models, large-scale simulation data, and production software used directly by engineers.

The Role

We’re looking for a backend engineer who enjoys building systems that sit between data infrastructure and real product features.

This role spans two major areas:

Data generation systems

• Build pipelines that generate and process large datasets used for training and evaluating models

• Manage simulation outputs, geometry data, and experiment artifacts

• Develop tools for validating, transforming, and curating datasets

Product backend

• Build and maintain APIs used by the Vinci product

• Develop integrations with models, simulation engines, and external tools

• Design services that support the core user workflows of the platform

You’ll work across the stack with ML engineers, physics researchers, and product engineers.

What We’re Looking For

• We value engineers who are comfortable moving between infrastructure, data systems, and product code, and who enjoy building pragmatic systems that ship.

• Backend Engineering

• Experience building and operating production backend services

• Strong experience designing APIs and service architectures

• Ability to write clean, maintainable, well-tested code

• Experience debugging and improving performance, reliability, and observability

• Comfortable integrating external services, APIs, and internal models

• Ability to work across teams to translate product requirements into system design

• Data & Pipeline Systems

• Experience building data pipelines or large-scale processing workflows

• Familiarity with batch processing, distributed systems, or workflow orchestration

• Experience managing large datasets and data transformations

• Comfort working with compute-heavy workloads and long-running jobs

• Systems & Infrastructure

• Experience deploying and operating systems in cloud environments (AWS, GCP, or similar)

• • Familiarity with containerized services and modern deployment workflows Ability to design systems that balance throughput, latency, and cost

• How We Work

• We’re a small team and engineers own large pieces of the system. That means:

• Designing systems, not just implementing tickets

• Shipping features that go directly into the product

• Working closely with researchers and customers