This role pays less than
58%
of similar roles. Most pay
$151,000–$224,875
— the shaded band above.
At the midpoint, this role pays about
$168k
versus about
$188k
for comparable roles.
Based on 240 similar postings.
Employer
About GEICO
GEICO (Government Employees Insurance Company) is one of the largest auto insurers in the United States, offering affordable auto, home, renters, and other personal insurance products. Industry: Insurance
GEICO currently has
89 open roles
on FindRole.
Listed pay typically runs
$110,000–$230,000
across 87 roles with salary data.
Senior Software Engineer, AI Agent Platform joins the AI Agent Platform team to build core infrastructure supporting enterprise-wide agentic workflows. This role focuses on developing distributed systems including an agent harness for durable execution, a retrieval-augmented generation platform for grounding agents in knowledge, an insight engine for processing execution data, an evaluation harness for measuring quality, and a skills marketplace for reusable capabilities. The candidate will design and own features across the full backend stack, ensuring reliability through observability, load testing, and on-call participation. Required expertise includes Python, Java, or Go, along with distributed systems fundamentals like concurrency and scalability. Preferred experience involves building GenAI applications using frameworks like LangGraph, managing RAG pipelines with engines like OpenSearch, and utilizing cloud platforms such as Azure or AWS to solve complex problems in the insurance domain.
What does a Software Engineer earn in California?
Median $214000 from 830 postings across 69 companies.
Design and deliver end-to-end platform components including agent harnesses, RAG systems, and evaluation frameworks.
Develop durable execution engines with state management, checkpointing, and retries for long-running agent workflows.
Build scalable RAG platforms to ground agents in enterprise data using ingestion, embedding, and retrieval services.
Create insight engines that transform agent execution data into live domain knowledge and context.
Build a multi-tenant skills marketplace where teams can publish, version, and reuse agent capabilities.
Implement reliability features including sandboxing, rate limiting, capacity planning, and automated monitoring for production systems.
Mentor junior and mid-level engineers to improve team engineering standards and technical execution.
Participate in on-call rotations to manage incidents, perform root cause analysis, and improve system reliability.
What we're looking for
Must have at least 5 years of professional software engineering experience building and operating production backend systems at scale.
Must have experience owning the design and delivery of services or major features end to end.
Must be proficient in one or more of Python, Java, Go, or comparable languages.
Must possess strong distributed systems fundamentals including concurrency, consistency, fault tolerance, data modeling, API design, and scalability.
Must have experience operating production services with CI/CD, automated testing, and Kubernetes or other container platforms.
Must have hands-on operational experience including observability, monitoring, alerting, on-call participation, incident response, and postmortems.
Must have experience scaling systems or improving reliability through SLOs, performance tuning, capacity planning, or eliminating recurring failure modes.
Experience with durable execution, GenAI applications, RAG systems, or SRE practices is preferred.