[Hiring] Software Engineer, Model Integrations @Foundry

Role Description

The next decade of film, episodic, and game production will be shaped by how well generative AI integrates into the pipelines artists already trust. Foundry's bet — backed by 30 years of building the tools behind every VFX Oscar of the last decade — is that the winners won't be standalone AI apps. They'll be the studios that can compose, control, and reason over a fleet of AI models inside their existing workflows, with the security and traceability production demands.

Griptape Nodes is the orchestration layer that makes that possible: a Python-first, node-based platform where artists assemble pipelines spanning image, video, 3D, audio, and text models — running locally or in the cloud, model-agnostic, and stitched into Nuke, Maya, Blender, and beyond. Griptape Studio is what comes next: a context layer that gives agents real production awareness so AI work can finally be coherent across an entire production.

As a Software Engineer on this team, you'll work on the surface artists touch most in Griptape Nodes: how they access and use AI models. Reporting to the Director of Engineering, you'll be the person who lands new model support on day one, translates technical model behavior into validation and error messages an artist can actually act on, and designs the next-generation interface for open-source and local models, including the deep local-model support that Griptape Studio and other parts of the platform will rely on for chat, agent loops, and more.

Our North Star is "Craveability." We build products people crave to use, not have to use. We measure success by how much users enjoy our products, not just tolerate them. Engineering is held to that bar — we keep users in flow, test the way they actually work, and build with the polish that earns trust.

Qualifications

• Strong Python with the engineering habits to back it up — type hints, tests, packaging, and dependency management aren't optional in your code.
• A degree in computer science.
• Customer empathy and intuition.
• Working knowledge of the modern model ecosystem — foundation models, diffusion, video and audio generators, model hubs (Hugging Face and friends).
• Hands-on experience with local inference tooling — Ollama, llama.cpp, vLLM, MLX, transformers, or equivalent.
• Generative AI fundamentals — diffusion models, LLMs and agents, fine-tuning, MCP, evaluation metrics, prompt engineering.
• A track record of using AI tools (Claude, Cursor, Copilot, agent frameworks) to genuinely accelerate your work.
• Strong written communication — clear design docs, useful PR descriptions, code comments.
• Comfort working across Windows, Linux, and macOS.

Requirements

• Experience shipping AI/ML integrations inside a product environment (nice to have, keen to learn).
• Familiarity with media and entertainment workflows and formats — OpenEXR, USD, ACES, OpenColorIO, common containers and codecs.
• Open-source contributions to ML or AI tooling.
• Working knowledge of model quantization, LoRA fine-tuning, or production model evaluation.
• Background in node-based, dataflow, or visual programming environments.
• Experience integrating with DCC tools (Nuke, Maya, Houdini, Blender).