Senior AI Engineer

Jobtailor; Austin (TX); On-site; USD 180,000 - 240,000; Full time

Job summary

Jobtailor in Austin, TX is seeking an experienced AI engineer to build agentic systems and production-grade tooling. You will own quality criteria, evaluation frameworks, and deployment patterns across teams.

The role requires 8+ years, strong Python, and hands-on experience with multi-agent architectures, tool calls, and reliable software. You will collaborate with product, security, and platform teams to deliver secure, scalable AI-enabled features.

Qualifications

• 8+ years of industry experience.
• Strong Python expertise.
• Solid software engineering fundamentals.
• Proven track record of delivering production systems.
• Hands-on experience building model-based and agentic systems in production environments.
• Experience with tool calling, structured outputs, retrieval, orchestration, and multi-agent architectures.
• Ability to define AI quality criteria, build evaluation frameworks, interpret results, and identify real-world failure modes.
• Data-driven prompt and context engineering experience.
• Strong understanding of the current AI model landscape.
• Ability to make pragmatic decisions across providers, architectures, cost, latency, reliability, and quality requirements.
• Working knowledge of MCP or comparable tool protocols.
• Experience with agentic development environments.
• Understanding of security implications of giving models access to tools and enterprise systems.
• Regular use of AI coding agents with critical review practices.
• Accountability for correctness, security, and maintainability of delivered software.
• Deep understanding of AI failure modes including hallucinations, context degradation, prompt injection, non-determinism, and silent regressions.
• Effective mitigation strategies for common AI failure modes.
• Strong communication skills.
• Ability to engage with technical and non-technical stakeholders.
• Collaborative mindset for working across EMEA teams.

Responsibilities

• Build agentic capabilities for TeamViewer Tia and the Agentic Ecosystem, including orchestration, tool use, retrieval, memory, and multi-step task execution
• Define quality criteria, build datasets and evaluation harnesses, and use evaluation results to guide release decisions
• Engineer model context through retrieval strategy, chunking, ranking, caching, compaction, and prompt assembly
• Improve quality through systematic iteration on prompts, tool design, model selection, and orchestration patterns
• Take AI capabilities to production and manage latency, cost, rate limits, fallback behavior, and quality drift
• Partner with product management, security, and platform teams to deliver secure, reliable AI-enabled features
• Apply fine-tuning or smaller specialized models where evaluation evidence supports it
• Work agent-first in engineering and help maintain team context, tooling, and delivery patterns
• Help shape high-quality agentic engineering practices across EMEA teams

Skills

Strong Python expertise

Proven track record of delivering prod

Hands-on agentic systems in production

Tool calling, structured outputs, and

Tools

MCP Tool Protocols

AI Coding Agents

Job description

• Build agentic capabilities for TeamViewer Tia and the Agentic Ecosystem, including orchestration, tool use, retrieval, memory, and multi-step task execution
• Define quality criteria, build datasets and evaluation harnesses, and use evaluation results to guide release decisions
• Engineer model context through retrieval strategy, chunking, ranking, caching, compaction, and prompt assembly
• Improve quality through systematic iteration on prompts, tool design, model selection, and orchestration patterns
• Take AI capabilities to production and manage latency, cost, rate limits, fallback behavior, and quality drift
• Partner with product management, security, and platform teams to deliver secure, reliable AI-enabled features
• Apply fine-tuning or smaller specialized models where evaluation evidence supports it
• Work agent-first in engineering and help maintain team context, tooling, and delivery patterns
• Help shape high-quality agentic engineering practices across EMEA teams

Requirements

• 8+ years of industry experience
• Strong Python expertise
• Solid software engineering fundamentals
• Proven track record of delivering production systems
• Hands-on experience building model-based and agentic systems in production environments
• Experience with tool calling, structured outputs, retrieval, orchestration, and multi-agent architectures
• Ability to define AI quality criteria, build evaluation frameworks, interpret results, and identify real-world failure modes
• Data-driven prompt and context engineering experience
• Strong understanding of the current AI model landscape
• Ability to make pragmatic decisions across providers, architectures, cost, latency, reliability, and quality requirements
• Working knowledge of MCP or comparable tool protocols
• Experience with agentic development environments
• Understanding of security implications of giving models access to tools and enterprise systems
• Regular use of AI coding agents with critical review practices
• Accountability for correctness, security, and maintainability of delivered software
• Deep understanding of AI failure modes including hallucinations, context degradation, prompt injection, non-determinism, and silent regressions
• Effective mitigation strategies for common AI failure modes
• Strong communication skills
• Ability to engage with technical and non-technical stakeholders
• Collaborative mindset for working across EMEA teams

Core Competencies

Demonstrates expertise in building and deploying agentic systems, with a strong focus on AI quality criteria, evaluation frameworks, and production-level software engineering. Proficient in Python and experienced in collaborating with cross-functional teams to deliver secure and reliable AI-enabled features.

Highest-signal resume keywords

• Python Expertise
• Production Systems Delivery
• AI Quality Criteria Definition
• Model-Based Systems Engineering
• Multi-Agent Architecture Experience

ATS Optimization Keywords

Hard Skills

• Software Engineering Fundamentals
• Data-Driven Prompt Engineering
• Context Engineering
• Tool Calling
• Orchestration Patterns
• Evaluation Frameworks
• AI Model Landscape Understanding
• Agentic Development Environments
• AI Failure Modes Mitigation
• Critical Review Practices

Soft Skills

• Strong Communication Skills
• Collaborative Mindset

Industry Keywords

• Agentic Ecosystem
• Quality Drift
• Latency Management
• Cost Management
• Security Implications

Tools & Technologies

• MCP Tool Protocols
• AI Coding Agents