Technical Lead

Certus Recruitment Group

Austin (TX)

On-site

USD 120,000 - 180,000

Full time

5 hours ago
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Job summary

Certus Recruitment Group is partnering with an Austin-based technology organization investing in AI, advanced automation and agentic engineering to build frontier AI models and AI agents in production.

We are seeking a senior engineer who remains hands-on, leads architecture and standards, and helps steer the roadmap while guiding a growing engineering team.

You will work across languages like Python, .NET, and contribute to evaluation, testing, and safeguards in production environments.

Qualifications

  • 5–8 years hands-on software engineering experience.
  • Prior technical leadership experience; Lead title isn’t required.
  • Strong software engineering fundamentals.
  • Practical experience building agentic AI systems in production.
  • Experience with AI agents performing substantive work within engineered constraints.
  • Understanding of failure modes and how to test, validate and safeguard autonomous systems.
  • Ability to write clean, maintainable production-quality code.
  • Comfortable across languages and frameworks like Python, .NET or similar.

Responsibilities

  • Leading projects across the agentic AI platform.
  • Designing and building production-grade AI agent systems.
  • Defining architecture, interfaces and technical direction.
  • Establishing evaluation, testing, validation and safeguards approaches.
  • 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.

Skills

Software engineering
Technical leadership
Production-grade systems

Job description

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
What we're looking for:
  • 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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