Technical Lead - Agentic AI
Listed on 2026-09-07
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Software Development
AI Engineer (Applied/Software), Software Architect, AI Reliability/ Performance Engineer, Machine Learning/ ML Engineer
Technical Lead - Agentic AI
Austin, TX
$140,000-$170,000 Salary
Certus Recruitment is partnering with an Austin-based technology organization making a significant investment in AI, advanced automation and agentic engineering.
They're building frontier AI models and AI agents directly into their core technology environment - not as experiments, but as systems performing meaningful work in production environments where accuracy, reliability and performance matter.
They're now looking for a senior engineer to help shape what comes next.
This is a technical leadership role, but it's not a move away from coding.
You'll remain highly hands-on while helping establish the architecture, engineering standards and operating patterns that allow autonomous and semi-autonomous AI agents to work reliably within carefully engineered constraints.
What you'll be doing:- Leading projects across the agentic AI platform
- Designing and building production-grade AI agent systems
- Defining architecture, interfaces and technical direction
- Establishing approaches to evaluation, testing, validation and safeguards
- Helping determine how AI-generated engineering work is constrained and verified
- Removing technical roadblocks and driving development forward
- Influencing the AI and engineering roadmap
- Helping hire and develop the engineering team as it grows
- Working directly with technical and business stakeholders
- 5-8 years' hands-on software engineering experience
- Previous technical leadership experience - a formal Lead title isn't necessary
- Strong software engineering fundamentals
- Practical experience building agentic AI systems that have operated in production
- Experience with AI agents performing substantive work within engineered constraints
- An understanding of where autonomous systems fail and how to test, validate and safeguard their output
- Ability to write clean, maintainable, production-quality code
- Comfortable working across languages and frameworks - potentially including Python, .NET or similar environments
You don't need to have completed an organization's entire transition to agentic engineering - very few people have.
What matters is that you've actually started doing it, encountered the real-world problems and developed informed technical opinions from production experience.
This is a rare opportunity to remain deeply technical while having significant influence over how an organization designs, governs, validates and deploys agentic AI.
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