Founding Applied AI Software Engineer

Applied AI Software Engineer

Location:
San Jose, California / Hybrid

About Kerrigan Robotics

Kerrigan is an AI-powered, robot agnostic orchestration platform that enables the ability to control all your robotic (AGV/AMR/Tugger/Forklifts/Drones/Humanoids) and data infrastructure (MES/WMS/ERP) needs. This AI powerhouse allows for minimal programming effort from the user and ramp up time up to 70% faster to production. While the industry focuses on building robots (product), Kerrigan has focused on bringing all robots and automation together through harmonious communication and routing. This allows perfection in routing traffic, communicating to your production lines, ERP, WMS, WCS, MES, AS/RS, and much more with unlimited expansion potential throughout your enterprise-level company. We help to make automating your factory simpler and more reliable!

Our team first did this with Tesla. They helped scale automation across Tesla’s factories worldwide ($5B worth of equipment with thousands of robots). Kerrigan also achieved this at Rivian, who now has multi-branded robots (65 robots) all working together and communicating seamlessly with their ERP and lineside controls. Many others are in the works this year in the food and beverage industry, defense, automotive, and others.

We had a successful pre-seed funding round in Q4 2025, and have been building the company, team, and platform at rapid pace.

The Role

As an
Applied AI Software Engineer
, you sit at the intersection of Machine Learning and robust Software Engineering. Your goal is to move AI out of notebooks and into production. You will be responsible for building the applications that leverage modern LLMs and Vision models, fine-tuning them for specific industrial use cases, and ensuring they run efficiently on our edge-to-cloud platform.

Key Responsibilities

- AI Application Building:
Develop software that integrates modern AI tooling (Vector DBs, RAG, Agentic frameworks) into the Kerrigan ecosystem.
- Model Optimization:
Perform
fine-tuning
and quantization of open-source models to optimize for specific robotics tasks.
- Deployment:
Work with the Platform team to deploy models on
NVIDIA Orin/Jetson
or cloud GPUs using TorchServe, ONNX, or TensorRT.
- Data Pipelines:
Build the infrastructure to collect, clean, and version-control data from physical sensors for model retraining.

Requirements

- Experience:
4+ years of software engineering, with at least 2 years focused on AI/ML implementation.
- Modern AI Stack:
Hands-on experience with frameworks like
PyTorch
, HuggingFace, and LangChain/LlamaIndex.
- Fine-Tuning:
Proven experience fine-tuning LLMs or Vision models (LoRA, QLoRA) for niche domains.
- Software Rigor:
Strong coding skills in
Python
and
Go
.
- Physical AI (Plus):
Experience with Computer Vision (OpenCV), point cloud processing, or deploying AI on physical hardware/edge devices is a significant advantage.

What This Role Is Not

- This is
not
a pure Research Scientist role; we value shipping functional products over publishing papers.
- This is
not
a data labeling role; you are building the systems that use the data.