Senior AI Engineer: Scalable AI & Automation

TeamViewer; Austin (TX); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Competitive compensation

Flexible PTO

401(k) with matching

Comprehensive health insurance

Parental leave

Job summary

TeamViewer seeks an experienced software engineer to build AI-powered capabilities for the TeamViewer Tia and broader AI platform. You will design services that enable intelligent workflows, automation, and seamless user experiences while defining testing strategies to ensure quality, reliability, and performance.

You will drive improvements to AI solutions through experimentation, iteration, and data-driven decisions, and optimize services for scalability and cost efficiency in production.

Qualifications

• 7+ years of software engineering experience with Python.
• Hands-on experience building AI-powered applications or platforms.
• Experience with LLMs, retrieval systems, and workflow orchestration.
• Ability to measure success metrics and optimize performance.
• Strong understanding of distributed systems and cloud-based apps.

Responsibilities

• Build AI-powered capabilities for TeamViewer Tia and AI platform.
• Design services for intelligent workflows and seamless UX.
• Define testing strategies to ensure reliability and performance.
• Improve AI solutions via experimentation and data-driven decisions.
• Optimize services for scalability and cost efficiency.
• Collaborate with product, platform, and security teams on secure features.
• Contribute to engineering best practices and AI-assisted tooling.

Skills

Python

AI platforms

Distributed systems

Cloud-based apps

Testing & performance

Collaboration

Job description

TeamViewer seeks an experienced software engineer to build AI-powered capabilities for the TeamViewer Tia and broader AI platform. You will design services that enable intelligent workflows, automation, and seamless user experiences while defining testing strategies to ensure quality, reliability, and performance.

You will drive improvements to AI solutions through experimentation, iteration, and data-driven decisions, and optimize services for scalability and cost efficiency in production.