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NEXTMOVEFDE careers · United States
Geico

Staff Machine Learning Engineer, AI Agent Platform

AI summary of the role

Build the next-generation enterprise AI Agent OS and SDKs at GEICO, designing scalable multi-tenant backend systems for agent workflows, skill ecosystems, harness engineering, and governance.

No longer in the current catalog. Last included 2026-09-09. Check the employer’s posting for availability.

What you’ll do

  • Architect scalable multi-tenant backend systems for AI agent workflows including configuration, evaluation, synthetic data generation, MCP server registry, A2A communication, and guardrail enforcement using AKS, FastAPI, etc.
  • Build an enterprise AI agent skill ecosystem with an internal skill marketplace for authoring, publishing, discovering, versioning, and governing reusable skill packages.
  • Implement production-grade AI agent harnesses covering tool dispatch, context management, error recovery, session state, and sub-agent coordination.
  • Develop observability frameworks with LLM-specific telemetry (token usage, latency, hallucination detection, behavior auditing) using OpenTelemetry and distributed tracing.

What you’ll bring

  • 6+ years designing, implementing, and maintaining multi-tenant AI/ML systems in production.
  • 6+ years with cloud platforms (Azure, AWS) and backend systems (Kubernetes, Temporal, OpenSearch, PostgreSQL, Redis, Neo4j).
  • Deep proficiency in Python, Java, or Go.
  • Proficiency in AI/ML and agentic frameworks (TensorFlow, PyTorch, LangGraph, CrewAI, AutoGen).

Technologies

AKS · FastAPI · Kubernetes · Temporal · OpenSearch · PostgreSQL · Redis · Neo4j · Python · Java · Go · TensorFlow

About Geico

Third-largest US auto insurer, selling personal auto and property coverage direct-to-consumer to millions of drivers; a wholly owned Berkshire Hathaway subsidiary.

Acquired · 5000+ people

Source and classification

Internal deployment & tooling · Evidence for this classification:

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 through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose. 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. Staff Machine Learning Engineer, AI Agent Platform The GEICO AI Agent Platform team is seeking an exceptional Staff ML Engineer to build the next generation enterprise AI Agent OS and SDKs. You will design, implement, and maintain scalable backend systems that enable business, product, and engineering teams to build, test, and
More from the job description

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 through relentless innovation to exceed our customers’ expectations while making a real impact for our company through our shared purpose. 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. Staff Machine Learning Engineer, AI Agent Platform The GEICO AI Agent Platform team is seeking an exceptional Staff ML Engineer to build the next generation enterprise AI Agent OS and SDKs. You will design, implement, and maintain scalable backend systems that enable business, product, and engineering teams to build, test, and deploy their own AI agents & workflows. In 2026, the agentic AI landscape is maturing rapidly — with standardized protocols (MCP, A2A), AI agent skill ecosystems, harness engineering, context engineering, and governance-first design becoming table stakes. You will help GEICO stay at the forefront. The candidate must have excellent communication skills and a proven track record of delivering business value via technical excellence. Key Responsibilities Platform Engineering Architect scalable mult [... source excerpt omitted ...] les. Implement an internal skill marketplace with search/discovery, quality scoring, security vetting pipelines, approval workflows, and progressive disclosure loading. Implement production-grade AI agent harnesses — the non-model infrastructure (tool dispatch, context management, error recovery/self-healing, session state, sub-agent coordination) that makes AI agents reliable for long-running tasks. Design feedforward guides (linters, type checkers, architecture constraints) and feedback sensors (test execution, LLM-as-judge, semantic analysis) mixing computational and inferential controls. Build and optimize context engineering systems — memory hierarchies (short-term, working, [... source excerpt omitted ...] ining on platform capabilities. Collaborate cross-functionally with data scientists, engineers, and product teams. Translate complex technical concepts for diverse stakeholders. Qualifications Technical Skills Bachelor's in CS, Engineering, or related field; advanced degree highly desirable. 6+ years designing, implementing, and maintaining multi-tenant AI/ML systems in production. 6+ years with cloud platforms (Azure, AWS) and backend systems (Kubernetes, Temporal, OpenSearch, PostgreSQL, Redis, Neo4j). Deep understanding of Docker, Prometheus, and OpenTelemetry. Deep proficiency in Python, Java, or Go. Extra credit for effectively leveraging AI coding tools (Cursor, Claude Cod

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