Lead Software Automation / Toolchain Engineer

Grafton Sciences•San Francisco, CA

72d

About The Position

We’re building AI systems with general physical ability — the capacity to experiment, engineer, or manufacture anything. We believe achieving this is a key step towards building superintelligence. With deep technical roots and real-world progress at scale (e.g., a $42M NIH project), we’re pushing the frontier of physical AI. Joining us means inventing from first principles, owning real systems end-to-end, and helping build a capability the world has never had before. We’re seeking a Software/Tooling Lead Engineer to automate and unify engineering workflows across EDA tools. You’ll build adapters, scriptable APIs, deterministic workflows, error parsers, and structured interfaces that make complex engineering tools callable by agents. This role is ideal for someone who can navigate diverse engineering software, wrap them into reproducible pipelines, and design the automation layer that sits between ML agents and real engineering tools.

Requirements

Experience automating engineering or scientific tools (e.g., CAD, EDA, CAE, CAM, COMSOL) using scripting, APIs, or workflow orchestration.
Strong systems-thinking ability and comfort working across heterogeneous domain tools, file formats, and execution environments.
Demonstrated ability to build reproducible, fault-tolerant automation pipelines and structured tool interfaces.
Comfortable working with ML, simulation, and tooling platform teams to bridge real engineering tools into agent-driven workflows.
Above all, we look for candidates who can demonstrate world-class excellence.

Responsibilities

Build automation pipelines and adapters for EDA and other tools, enabling programmatic and deterministic execution.
Develop structured APIs, log parsers, error classifiers, and reproducible workflows that integrate seamlessly with orchestration and agent systems.
Implement tool-wrapping scripts, automated validation routines, and parameterized flows across commercial and open-source engineering platforms.
Collaborate closely with tooling platform engineers, agent systems, ML teams, and domain experts to integrate automated toolchains into real workflows.