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Staff Engineer, Storage Metadata and Context

  • Emeryville, CA, United States

$182,835 to $236,610 USD / year

This opening has closed.

The original listing is kept below for reference.

Job details

Pay
$182,835 to $236,610 USD / year
Experience
3+ Years of Software-Driven Infrastructure: Recent experience in scale environments where you've transitioned manual workflows into programmatic, API-driven services
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

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. Disclaimer This position is with Pixar, which is part of a business we call PIXAR Animation Studios. To learn more about Disney's guidelines on the use of AI for candidates, click here. Pixar is an equal opportunity employer. Applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Disney champions a business environment where ideas and decisions from all people help us grow, innovate, create the best stories and be relevant in a constantly evolving world.

DISABILITY ACCOMMODATION FOR EMPLOYMENT APPLICATIONS

The Walt Disney Company and its Affiliated Companies are Equal Employment Opportunity employers and welcome all job seekers including individuals with disabilities and veterans with disabilities. If you have a disability and believe you need a reasonable accommodation in order to search for a job opening or apply for a position, visit the Disney candidate disability accommodations FAQs. We will only respond to those requests that are related to the accessibility of the online application system due to a disability. Having technical issues? View the FAQs for help.

More about this job

Skills

  • NAS
  • Communication skills
  • Workflow
  • Troubleshooting
  • IBM Middleware
  • Apache Kafka
  • Elasticsearch
  • Back-end development
  • Programming languages
  • Python
  • Docker
  • Kubernetes
  • AWS
  • Content creation

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