Senior Applied AI Engineer - GenAI Security Product

LiveView Technologies

Seattle (WA)

On-site

USD 185,000 - 232,000

Full time

14 days+
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Job summary

LiveView Technologies is seeking a Senior Software Engineer, Applied AI to own end-to-end delivery of a GenAI-powered security deterrence product. You will shape the product that sits atop the perception stack, guiding from design through production and field iteration with a focus on precision, safety, and reliability.

You will collaborate with backend, platform, ML/LLM Ops, and data teams, integrating detection models into shipped product while weighing build-vs-buy decisions under real cost

Qualifications

  • 6+ years building and shipping production software
  • Strong Python and API design judgment
  • Experience with end-to-end delivery of product features
  • Experience collaborating with ML/data teams

Responsibilities

  • Own GenAI-powered security product from design through production and field iteration.
  • Build and own the detection-to-response harness and orchestration, including voice generation and evaluation.
  • Own the precision and safety bar for real-world actuation systems.
  • Design and build services, APIs, and integration code wrapping detection and voice into a product.
  • Collaborate with ML scientists and data teams; advise build-vs-buy decisions.

Skills

Python
TypeScript/Node
APIs
Production backend systems
Cross-functional collaboration
End-to-End delivery

Education

Bachelor's or Master's in Computer Science, Engineering, or related field

Job description

LiveView Technologies is seeking a Senior Software Engineer, Applied AI to own end-to-end delivery of a GenAI-powered security deterrence product. You will shape the product that sits atop the perception stack, guiding from design through production and field iteration with a focus on precision, safety, and reliability.

You will collaborate with backend, platform, ML/LLM Ops, and data teams, integrating detection models into shipped product while weighing build-vs-buy decisions under real cost

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