Staff Machine Learning Engineer

GEICO GEICO · Insurance · Palo Alto, CA +1

Staff ML Engineer to lead Generative AI applications at GEICO, focusing on designing, developing, and deploying scalable LLM and agentic systems for business value. Role involves end-to-end ownership, collaboration, and technical leadership.

What you'd actually do

  1. Own end-to-end design, development, and maintenance of high-performance AI solutions that use agentic workflows to deliver concrete business value for internal stakeholders and customer-facing applications. Examples include AI agent orchestration, conversational AI solutions, knowledge assistants, process assistance and automation, etc.
  2. Collaborate with cross-functional teams, including data scientists, ML engineers, software engineers, product managers, and designers to gather requirements, define project scope and prioritize feature development. Establish pragmatic technical visions and roadmaps that balance business outcomes, product release timelines, and engineering excellence.
  3. Integrate and build solutions using GEICO’s AI platform architecture. Partner with platform teams to communicate requirements, understand current capabilities and gaps, and contribute to platform feature roadmaps and development.
  4. Ideate, define, and build first-of-its-kind solutions within GEICO, with a deep understanding of business and technical processes, applications, and architecture to guide development.
  5. Drive the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.

Skills

Required

  • Python
  • Java
  • LangSmith
  • LangGraph
  • A2A
  • MCP

Nice to have

  • Azure
  • AWS
  • eval frameworks
  • agent tooling
  • RAG pipelines
  • prompt engineering
  • no code/low code development
  • high-code development
  • insurance domain

What the JD emphasized

  • 8+ years of experience designing and building scalable production AI/ML applications and systems in cloud environments
  • 5+ years owning end-to-end development, monitoring, maintenance, and continuous improvement of scalable, robust AI/ML applications.
  • 5+ years of experience with training, finetuning, real-time/batch inferencing, and evaluation systems for AI/ML models and LLMs used in production systems
  • 5+ years of experience managing the end-to-end software development life cycle (e.g. CI/CD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for Generative AI applications, backend systems, and APIs
  • Experience using frameworks to build LLM-based agentic workflows such LangSmith/LangGraph or similar
  • Experience using typical agentic communication standards such as A2A, MCP, and similar to design, architect, and build working multi-agent applications

Other signals

  • Generative AI applications
  • LLM, agentic, and knowledge-search capabilities
  • agent orchestration
  • conversational AI solutions
  • knowledge assistants
  • process assistance and automation