Applied AI Engineer

Siza- Buso ConsultingAustin, TX
1dHybrid

About The Position

Job Summary Location: Austin, TX (Hybrid – 3 days in office) Software engineering is changing fast. AI tools can already help with small tasks. But the real opportunity isnt in isolated prompts — its in redesigning how mission-critical systems are built, maintained, and scaled using AI as a first-class engineering capability. Were looking for an exceptional Applied AI Engineer to help answer a fundamental question: What does it look like for a high-performance engineering team building institutional-grade financial software to use AI to its full potential — without compromising quality, security, or reliability? What you will do This is a hands-on engineering role. You will ship production code while simultaneously embedding AI deeply into how we operate. You will:

Requirements

  • Youre a strong engineer first.
  • Youve already shipped and owned meaningful production systems.
  • You think in architectures, trade-offs, and failure modes — not just features.
  • System design comes naturally to you.
  • Youre deeply excited about how AI is reshaping software engineering. Not casually interested — genuinely obsessed.
  • You experiment constantly.
  • Youve likely built your own agents, internal tooling, or AI-powered workflows simply because you couldnt resist.
  • You: Code daily and enjoy it.
  • Have strong production instincts and know what good looks like.
  • Care about code quality, correctness, and reliability.
  • Take pride in unblocking others and increasing team leverage.
  • Think about optimization, efficiency, and long-term engineering velocity.
  • Are comfortable operating in ambiguity and turning emerging ideas into production-ready systems.
  • Treat AI infrastructure like any other critical backend system — versioned, observable, reproducible, and safe.
  • You likely have open-source contributions, side projects, or public experiments demonstrating how you use AI in real engineering environments.
  • You dont just use AI tools. You engineer workflows around them.

Responsibilities

  • Build AI-powered engineering workflows that meaningfully accelerate delivery without sacrificing reliability or correctness.
  • Design and deploy agent-based systems, orchestration layers, and AI-assisted tooling that operate in real production environments.
  • Contribute directly to core product code , using AI to amplify your own impact and prove out the workflows you introduce.
  • Systematize AI usage across the team , turning ad hoc experimentation into consistent, high-quality processes with guardrails and observability.
  • Prototype AI-enabled product features , partnering closely with product and engineering.
  • Continuously evaluate emerging models and tools , exercising strong judgment about what to adopt and what to ignore.
  • Engineer AI infrastructure as a production system , including CI/CD integration, configuration management, and safe rollout strategies.
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