Senior AI Platform Engineer - Agent Harness & RAG

GEICO; Maryland; Hybrid; USD 105,000 - 230,000; Full time

Job summary

GEICO is seeking a Senior Software Engineer to build and own the AI Agent Platform, including an agent harness, RAG platform, and insight engine. You will design durable, scalable backend services, mentor engineers, and work with product managers and data scientists to turn requirements into platform features.

The role emphasizes end-to-end ownership, production reliability, and hands-on experience with GenAI workflows and distributed systems at scale.

Qualifications

• 5+ years of professional software engineering experience building and operating production backend systems at scale.
• Experience owning the design and delivery of services or major features end to end.
• Strong proficiency in one or more of Python, Java, Go, or comparable languages.
• Experience operating production services with CI/CD, automated testing, and Kubernetes or other container platforms.

Responsibilities

• Own the design and delivery of significant platform components and features end to end, from technical design and API definition through implementation, rollout, and iteration.
• Mentor junior and mid-level engineers, and help raise the engineering bar on the team.
• Collaborate with product managers, data scientists, and consuming teams to understand workflow needs and translate them into platform features.
• Build and own work in areas such as agent harness, RAG platform, and insight engine to power enterprise use cases.
• Operate production health, define SLIs/SLOs, and implement observability and on-call processes.

Skills

Backend engineering

Python

Java

Go

Distributed systems

Kubernetes

Tools

Kubernetes

Job description

GEICO is seeking a Senior Software Engineer to build and own the AI Agent Platform, including an agent harness, RAG platform, and insight engine. You will design durable, scalable backend services, mentor engineers, and work with product managers and data scientists to turn requirements into platform features.

The role emphasizes end-to-end ownership, production reliability, and hands-on experience with GenAI workflows and distributed systems at scale.