AI Engineer (Backend TypeScript or Python) -Austin, TX/ Sunnyvale, CA

Title: AI Engineer (Backend TypeScript or Python)

Location: Austin, TX/ Sunnyvale, CA (Hybrid 3 days On-Site and 2 days Remote) Need Local candidates only

Duration: 12 Months

Job Description

AI Engineer (Backend TypeScript or Python)

  - Strong backend engineering in TypeScript/Node.js (preferred) or Python, with production API design experience

  - Has built LLM harnesses/scaffolds with agentic loops, RAG pipelines, and tool-calling architectures

  - Experience designing multi-agent systems and integrating LLMs with internal/external APIs

  - Bonus: AI platform/developer tooling, evaluation & observability frameworks, AI security & guardrails

Senior AI Engineers

Looking for senior-level ICs with:

• Experience building AI-powered features into production web applications.
• Ability to design and implement:
  • Context-aware chat interfaces
  • RAG-based systems
  • Enterprise integrations
• Comfortable operating in:
  • TypeScript-heavy environments (preferred)
  • Python environments with willingness to adopt TypeScript

Additional expectations:

• Strong use of Claude and AI-assisted development workflows.
• Skilled at:
  • Prompting
  • Structuring tasks
  • Reviewing and validating generated code

Tech Stack & AI Approach

Language & Stack Preferences

• Primary preference is TypeScript across both frontend and backend engineering.
• Reasoning:
  • Aligns with existing Places frontend/backend teams.
  • Enables shared codebases and engineering consistency.
• Python perspective:
  • Hiring manager personally sees Python as more flexible.
  • However, TypeScript remains the preferred language for this environment.
• Strong Python engineers are still viable if they:
  • Are willing to learn TypeScript.
  • Understand that much of the existing codebase is TypeScript-based.

AI Tools & Engineering Practices

• Team heavily uses Claude for software development.
• Core philosophy:
  • “Coding is cheap.”
• Greater emphasis is placed on:
  • Architecture and planning
  • Strong testing strategies
  • Validation and integration quality
• Workflow approach:
  • Claude generates much of the implementation code.
  • Engineers focus on task structuring, prompting, testing, and validation.

Desired Technical Familiarity

Candidates should ideally have exposure to:

• RAG (Retrieval-Augmented Generation)
• Enterprise AI integration patterns
• Apple ecosystem/platform concepts, including:
  • MCPs
  • FCP servers

Manager specifically noted they do not want to teach these concepts from scratch.