Job Description

TeamViewer provides a leading Digital Workplace platform that connects people with technology—enabling, improving and automating digital processes to make work work better. Our software solutions harness the power of AI and shape the future of digitalization.

We believe that our diverse teams and strong company culture are key to the success of our products and technologies, that hundreds of millions of users around the world and around 645,000 customers across all industries rely on. With more than 1,900 employees worldwide, we celebrate the unique perspectives and talents that each individual brings to the table and foster a dynamic work environment where new ideas thrive. Are you ready to join our team and make an impact?

At TeamViewer, we build technology that helps organizations connect people, devices, and digital workflows securely and efficiently. Our products support teams that need to manage complex IT environments, resolve disruptions faster, and automate work with confidence.

The Agentic Ecosystem team is building the foundation for AI-native enterprise software. We create platform capabilities that allow AI agents to understand context, discover tools, invoke capabilities, and execute governed actions across TeamViewer products and connected third-party systems.

The work sits at the core of agentic experiences: MCP servers and clients, tool catalogs, context assembly, orchestration, evaluation, observability, secure integration patterns, and production-grade guardrails. The goal is to make agent behavior reliable, measurable, auditable, cost-aware, and safe for enterprise use.

You will help define how autonomous agents become trusted components of real-world software, not experiments or demos. This means combining strong engineering standards, AI-native development practices, human accountability, and customer trust. Join us if you want to build the ecosystem that will power the next generation of intelligent digital work.

Responsibilities

• Build the services behind TeamViewer's agentic ecosystem, including MCP servers and clients, tool integrations, context assembly, orchestration, and connections to external agent frameworks.
• Design and operate enterprise-grade AI systems with authentication, authorization, tenancy isolation, auditability, rate limiting, and cost controls.
• Create agent-friendly tool interfaces, schemas, and workflows, and validate their effectiveness through systematic evaluation.
• Build and maintain evaluation frameworks that assess prompts, tools, models, and retrieval strategies, using quality gates to support release decisions.
• Engineer and optimize production AI workflows with telemetry, monitoring, cost management, latency tracking, and quality drift detection.
• Implement safeguards against prompt injection, tool misuse, and other AI-specific security risks in collaboration with security stakeholders.
• Work across the full stack, building Python services and partnering on frontend experiences that bring AI capabilities to end users.
• Use AI coding agents as a core development mechanism and continuously improve the context, tooling, and engineering practices that enable them to perform effectively.

Requirements

• 8+ years of experience building production software with Python, combined with sufficient TypeScript expertise to contribute across the stack.
• Hands-on experience delivering model-based or agentic systems, including tool calling, structured outputs, retrieval, context management, and orchestration.
• Strong understanding of MCP or comparable agent-tool protocols, including the challenges of authorization, discovery, versioning, and multi-tenant environments.
• Proven ability to define quality criteria, build evaluation frameworks, interpret results, and continuously improve AI systems based on evaluation outcomes.
• Solid working knowledge of OAuth, service identities, event-driven architectures, and enterprise SaaS platforms.
• Regular use of AI coding agents, paired with a critical review mindset and accountability for software correctness, security, and maintainability.
• Deep understanding of AI-specific security risks, including prompt injection, tool abuse, excessive permissions, and data leakage through model context.
• Familiarity with common AI system failure modes such as hallucinations, context degradation, non-determinism, and silent regressions, along with effective mitigation strategies.
• Excellent English communication skills and the ability to collaborate effectively across globally distributed engineering teams.

What we offer

• Competitive compensation and bonuses
• Flexible PTO and paid holidays
• 401(k) with employer matching
• Comprehensive Health insurance package including 100% employer-paid medical coverage
• Up to 12 weeks of Parental Leave
• Basic Life Insurance, Short-Term & Long-Term Disability, 100% employer-paid
• Quarterly teambuilding events, leadership luncheons, and companywide “All Hands” meetings
• Open door policy and business casual dress code
• We celebrate diversity as one of our core values. Join c-a-r-e and lead change initiatives together with us!

Work location for this position is Austin, TX.

TeamViewer is an equal opportunities employer and is committed to building an inclusive culture where everyone feels welcome and supported. We C-A-R-E and understand that our diverse, values-driven culture makes us stronger. As we continue to grow as a company, we also focus on enabling our employees to grow both personally and professionally. We are proud to have an open and embracing workplace environment that will empower you to be your best no matter your gender, civil or family status, sexual orientation, religion, age, disability, education level, or race.

If you require any accommodations or adjustments during the application or hiring process, including interview or onboarding support, please reach out to your Talent Acquisition Partner, who will be happy to support you.