Sr. Software Engineer, AI Agent Platform

## Sr. Staff Software Engineer, AI Agent Platform Apply:
Hybrid:
New York City, NY:
Palo Alto, CA:
Bethesda, MD:
Seattle, WA:
Full time:
Posted Today:
R0063410
** Why Join GEICO?
** At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.

Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.

Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge:
Great Company, Great Culture, Great Rewards, and Great Careers.
** Sr. Staff Software Engineer, AI Agent Platform**  #
** Why Join GEICO?
** GEICO is transforming how AI is built and deployed across the enterprise. As one of the largest insurers in the United States, we are investing heavily in next-generation AI platforms that empower more than 30,000 associates and enhance experiences for millions of customers.

We are looking for a Sr. Staff Software Engineer with deep backend engineering and tech-lead experience to help build GEICO's enterprise AI Agent Platform. The team is building several core systems: an agent harness that runs agentic workflows durably in production, a retrieval-augmented generation (RAG) platform that grounds agents in enterprise knowledge, an insight engine that turns agent execution data and signals from related systems into live domain knowledge and context for both people and agents, an eval harness that measures agent quality and catches regressions, and a skills marketplace where teams publish and reuse agent capabilities.

Each of them is a distributed systems problem at its core. We care about your track record designing and building durable, scalable systems as well as your experience in AI/ML.  #
** The Opportunity
** As a tech lead on the AI Agent Platform team, you will own the design and delivery of one or several of the core systems that power use-case-agnostic agentic workflows across the enterprise, from claims and underwriting to internal associate tools. This is platform work: generalized services and capabilities that many teams build on, not a single agent application.

We welcome candidates from application, platform, or infrastructure backgrounds. What matters is that you have led the design of systems that stay correct, available, and operable under real production load, that you've been accountable for running them (on call, incidents, and all), and that you're comfortable working across the full backend stack. Hands-on experience building GenAI applications or agentic harnesses is a strong plus, and the foundation is systems judgment.  

#
** What You Will Do*
* ** Lead
* ** Lead the technical design and delivery of major platform components end to end, from architecture and API design through rollout, operation, and iteration.
* Drive design reviews, set engineering standards, and make sound tradeoff and build-vs-buy decisions for the platform.
* Mentor engineers and raise the engineering bar across the team and the teams building on the platform.
* Partner with product managers, data scientists, architects, and consuming teams to turn workflow needs into generalized platform capabilities.  
** Build
* * Depending on your strengths, you'll lead work in areas such as:
* Agent harness: the durable execution engine for agent workflows, with state management, checkpointing, retries, idempotency, and recovery for long-running, multi-step, tool-calling workflows.
* Agent harness integrations: services, APIs, and integration contracts (including protocols like MCP) that let many teams connect agents to internal services, data sources, and external systems consistently.
* RAG platform: shared ingestion, chunking, embedding, indexing, and retrieval services that ground agents in enterprise documents and data, with access controls, freshness guarantees, and low-latency retrieval at scale.
* Insight engine: pipelines and services that collect data from agent executions and related enterprise systems and turn it into continuously updated domain knowledge and agent context, served to people through dashboards and reports and to agents through retrieval and tool interfaces. Where the RAG platform grounds agents in…