Senior Staff Engineer, Interactive Voice Response - Ai/ml

GEICO GEICO · Insurance · Palo Alto, CA +2

Senior Staff Engineer to design, develop, and deploy large-scale distributed AI applications and multi-agent systems for customer self-service across voice, IVR, and chat channels. Requires strong software engineering background, experience with AI/ML frameworks, and deploying LLMs in production.

What you'd actually do

  1. Design, develop, and deploy large-scale distributed AI applications that power customer self-service across multiple communication channels (voice, IVR, chat).
  2. Build and optimize multi-agent systems that enable intelligent, collaborative decision-making to improve automation and customer experience.
  3. Collaborate with cross-functional teams (engineering, product, data science) to translate business requirements into scalable AI/ML solutions.
  4. Ensure system reliability, scalability, and performance through best practices in architecture, testing, and monitoring.
  5. Stay at the forefront of AI and distributed systems research, brining innovative approaches and tools into production environment.

Skills

Required

  • Python
  • SQL
  • NoSQL databases
  • Docker
  • Kubernetes
  • Azure tools and services
  • TensorFlow
  • PyTorch
  • Java
  • C++
  • LLMs
  • micro-services oriented architecture
  • extensible REST APIs
  • architecture and design
  • continuous delivery
  • infrastructure as code
  • PowerShell scripting
  • Azure Portal
  • application monitoring tools
  • performance assessments
  • Python framework
  • Java framework
  • AWS
  • GCP
  • Azure

Nice to have

  • mentor junior engineers
  • fast-paced, startup-like environment
  • developer tooling across the software development life cycle

What the JD emphasized

  • large-scale distributed AI applications
  • multi-agent systems
  • AI/ML frameworks and tools
  • deploying AI or machine learning models(LLMs) in production environments
  • building large-scale distributed systems
  • Azure or AWS

Other signals

  • large-scale distributed AI applications
  • multi-agent systems
  • customer self-service
  • production environments
  • Azure or AWS