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Software Engineer, AI Interactions; iOS), XR

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Towards AI, Inc.
Full Time position
Listed on 2026-06-09
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Software Engineer, Full Stack Developer
Salary/Wage Range or Industry Benchmark: 207000 - 300000 USD Yearly USD 207000.00 300000.00 YEAR
Job Description & How to Apply Below
Position: Staff Software Engineer, AI Interactions (iOS), XR

Staff Software Engineer, AI Interactions (iOS), XR Google

Published 28 Mar 2026

San Jose, CA, USA

207K - 300K USD Annual

Full Time

27500 - 275000 people

Role Highlights
  • AI
  • NLP
  • Generative AI
  • Information Retrieval
  • Vector Database
  • Computer Science
  • API
  • Full Stack
  • Product Design
  • Data Structures
  • System Design
  • Technical Leadership
  • Testing
  • PhD
  • RAG
  • LLMs
  • Search
  • Storage
  • Security
  • UI
  • UX
  • Research
Tools, Libraries and Frameworks
  • IOS
Description

The role involves empowering a team to develop reusable AI‑based interactive components and libraries for XR. This will build a foundation for other experiences on next‑generation devices. The individual will help drive the roadmap and execution, advocating for scalable architectures. Collaboration across product areas will be key to delivering foundational elements for future experiences.

Required Qualifications and Skills

The role requires a Bachelor's degree or equivalent practical experience, with 8 years of mobile application development experience for iOS. Additionally, 5 years of experience testing and launching software products, and 3 years of experience with mobile application design and architecture are necessary. Preferred qualifications include a Master's degree or PhD in a related technical field, 8 years of experience with data structures and algorithms, and 3 years of experience in a technical leadership role.

Experience developing and deploying Generative AI applications, including RAG pipelines, vector databases, and LLM interactions via APIs, is also preferred. Understanding the challenges of developing for mobile and resource‑constrained devices is beneficial.

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