Full-stack expertise in storage solutions, both physical and virtual, at petabyte scale.
In-depth knowledge of data access protocols: NFS, SMB, and S3, including file-locking and permissions.
Experience in building APIs (REST, gRPC) and middleware for storage applications.
Familiarity with Model Context Protocol (MCP) and AI tooling interfaces.
Proficient in metadata engineering, including schema design and indexing with Kafka, ElasticSearch, or Vector DBs.
3+ years in software-driven infrastructure, transitioning manual workflows to API-driven services.
Ability to translate creative needs into precise technical metadata queries.
Responsibilities
Architect and maintain software layers for AI agent interaction with NAS environments.
Lead the implementation of Model Context Protocol (MCP) servers for AI data access.
Design automated systems for semantic discovery and agentic connectivity.
Collaborate across technical and creative teams to enhance workflows.
Manage the synchronization of raw data and metadata as the library evolves.
Enable smart features like auto-tagging and similarity search within storage.
Participate in an on-call rotation for critical issues.
Benefits
Opportunity to work at the intersection of data platforms and AI.
Engagement in innovative projects that bridge traditional and modern technologies.
Collaborative environment with cross-disciplinary teams.
Focus on enhancing creative workflows through technology.
Full Job Description
As a Staff Engineer at the intersection of Data Platforms and AI, you will architect the software layers that enable our production-facing storage to become context-aware. Your mission is to design the APIs, Metadata services, and MCP implementations that allow AI agents to navigate and reason across Petabytes of high-value media assets. You will help to bridge the gap between traditional HPC protocols and a modern Agentic ecosystem.
RESPONSIBILITIES:
Architect Semantic Connectivity: Develop and maintain the software layer that exposes existing NAS environments (NFS, SMB, S3) to AI agents and LLM frameworks through modern API abstractions and MCPs
Implement Model Context Protocol (MCP): Lead the implementation of MCP servers to provide a standardized interface for AI models to safely and efficiently browse, read, and interpret data within our HPC storage
Semantic Discovery & Agentic Connectivity: Design automated systems to deconstruct the implicit context stored in long-path hierarchies and file headers, architecting the "connective tissue" (REST, gRPC, MCP) that enables AI agents to resolve complex creative queries without needing direct knowledge of underlying mount paths or protocols
Cross-Disciplinary Collaborator: Act as a critical "bridge" across technical storage teams, software tool designers, and creative artists—adapting your communication style to translate deeply technical concepts into practical, workflow-enhancing solutions for non-technical users
Data & Metadata Orchestration: Manage the state and relationship between raw file data and its digital twin in the metadata layer, ensuring that relational and semantic data remain in sync as the studio library evolves
Context Feature Enablement: Enable "smart" features within existing storage such as auto-tagging, similarity search, and automated summarizing
On-call: Ability to participate in an on-call rotation for critical issues
QUALIFICATIONS:
Full-Stack Storage Expertise: Ability to bridge the gap between the data center and the AI agent. You leverage your background in architecting, managing, and troubleshooting physical and/or virtual storage solutions to inform how agentic workflows and metadata pipelines access underlying data at petabyte scale
Broad Protocol Knowledge: Expertise in how data is accessed and managed across NFS, SMB, and S3. You understand the nuances of file-locking, permissions, and latency across different storage protocols
API & Middleware Development: Proven experience building APIs (REST, gRPC) and middleware that sit between raw storage and application layers
Model Context Protocol (MCP) & AI Tooling: Understanding of MCP and how to build tool-calling interfaces for LLMs
Metadata Engineering: Proven ability to design schemas and indexing pipelines using Kafka, ElasticSearch, or Vector DBs to represent physical files as semantic entities
3+ Years of Software-Driven Infrastructure: Recent experience in scale environments where you've transitioned manual workflows into programmatic, API-driven services
The Translator Mindset: Ability to translate abstract creative needs (e.g., "I need to see all iterations of this scene") into technical metadata queries that return precise results
Versatile Backend Development: High degree of comfort working across various programming languages to build the foundational "glue" that connects storage metrics and file data to agentic frameworks; deep proficiency in Python is a significant plus
PREFERRED SKILLS:
Modern AI Frameworks: Hands-on experience with agentic libraries, with a focus on building custom data connectors and Retrieval-Augmented Generation (RAG) architectures
Containerization & Orchestration: Experience with Docker and Kubernetes for scaling metadata extraction and embedding workers
HPC Awareness: Understanding of the performance characteristics of high-end storage (Vast, NetApp, StorageGrid, AWS) and how to minimize the overhead of metadata operations
Creative Pipeline Interest: A passion for digital content creation and an interest in how AI can accelerate and modernize production workflows
The hiring range for this position in Emeryville is $182,835.00 to $236,610.00 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors.
About Pixar
Pixar Animation Studios is an American computer animation studio that creates animated feature films, shorts, and television specials. The studio's headquarters are located in Emeryville, California. Pixar was founded in 1979 as the Graphics Group, part of the Lucasfilm computer division, before its spin-off as a corporation in 1986 with funding from Apple Inc. co-founder Steve Jobs. Pixar has produced 23 feature films, beginning with Toy Story in 1995, which was the first-ever computer-animated feature film. The studio has won numerous awards, including 11 Academy Awards, seven Golden Globe Awards, and 11 Grammy Awards.
