Senior Machine Learning Engineer, AI Agent Platform

Position: Senior Staff Machine Learning Engineer, AI Agent Platform
GEICO .
For more information, please .Senior Staff Machine Learning Engineer, AI Agent Platform page is loaded## Senior Staff Machine Learning Engineer, AI Agent Platform remote type:
Hybrid locations:
New York City, NY:
Palo Alto, CA:
Bethesda, MD:
Seattle, WAtime type:
Full time posted on:
Posted Todayjob requisition :
R0063410
** 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.
**** Sr. Staff Machine Learning Engineer – AI Agent Platform
**** Position Description
** GEICO is seeking an exceptional Sr. Staff ML Engineer to join our AI organization. You will serve as a technical leader and key architect for GEICO's virtual assistant platform that elevates productivity for 30K+ internal associates and the customer experience for millions of policyholders.
** Sr. Staff AI Agent Platform Engineers
** set the technical vision and drive the architecture of multi-tenant services that power the building, testing, deployment, and hosting of LLM-based AI agents. This includes multi-agent orchestration, standardized interoperability protocols (MCP, A2A), AI agent skill ecosystems with marketplace and governance capabilities, production-grade harness & context engineering, and guardrail frameworks for safe autonomous operation at enterprise scale.
** Responsibilities**
* ** Technical Vision & Architecture:
** Define the long-term technical strategy for GEICO's AI agent platform — including multi-agent orchestration, AI agent lifecycle management, evaluation frameworks, skill registries and marketplace, and workflow orchestration.
* ** AI Agent Skills & Marketplace:
** Architect an enterprise skill ecosystem — reusable capability packages that encode domain expertise and workflows into portable, discoverable modules. Build and govern an internal skill marketplace with versioning, security vetting, approval workflows, progressive disclosure loading, and usage analytics.
* ** Harness & Context Engineering:
** Lead design of production-grade AI agent harnesses (tool dispatch, context management, error recovery, session state, fine-grained Authn/AuthZ) that makes AI agents reliable for long-running workflows. Apply feed forward guides (linters, architecture constraints, spec-driven validation) and feedback sensors (test execution, LLM-as-judge) mixing computational and inferential controls. Design context engineering systems that treat the LLM context window as a managed resource — memory hierarchies, RAG pipelines, context compaction, scratchpads, and dynamic skill/tool loading.
* ** Platform & Interoperability:
** Own high-performance platform components powering end-to-end agentic workflows: MCP server/registry management, A2A communication infrastructure, prompt management, workflow orchestration, guardrail enforcement, and observability pipelines.
* ** AI Safety & Governance:
** Establish AI agent governance frameworks including bounded autonomy, human-in-the-loop escalation, audit trails, prompt guardrails, and RBAC/ABAC access controls. Extend governance to skill-level security — vetting published skills for hidden payloads, injection vectors, and data exfiltration risks.
* ** Leadership:
** Collaborate cross-functionally with data scientists, engineers, product managers, and designers. Mentor engineers at all levels. Elevate AI engineering best practices — including harness engineering patterns and agentic coding tools — across the company.
** Basic Qualifications
*** 8+ years of professional software development experience with at least two languages (Java, C++, Python, Go, or C#).
* 6+ years designing and building AI/ML platforms using open-source/cloud-agnostic components (Elasticsearch, Qdrant, Kafka, Postgre

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