Senior Machine Learning Engineer, AI Agent Platform

GEICO • New York, NY

4d • Remote

About The Position

GEICO is seeking an experienced Sr. ML Engineer to join our AI organization. You will play a key role in the development of GEICO's virtual assistant platform that elevates productivity for 30K+ internal associates and the customer experience for millions of policyholders. You will collaborate with a dynamic team of AI and software engineers to design, develop, and deploy systems that ensure productivity, scalability, and usability of GenAI workflows across GEICO. AI Agent Platform Engineers are responsible for building key multi-tenant services that power the building, testing, simulation, deployment, and hosting of LLM-based AI agents. This includes contributing to AI agent skill ecosystems, harness and context engineering infrastructure, interoperability layers (MCP, Skills), and guardrail systems- working closely with Staff and Sr. Staff engineers who set the broader architectural direction. The ideal candidate should demonstrate a proven track record of building high-performance Generative AI Systems and platforms.

Requirements

• 5+ years of professional software development experience with at least two general-purpose programming languages such as Java, C++, Python, or C#.
• 4+ years of experience designing and building AI/ML platforms and systems utilizing open-source/cloud-agnostic components such as search engines (e.g., OpenSearch, Milvus), data warehouses (e.g., Snowflake), streaming platforms (e.g., Kafka), relational databases (e.g., PostgreSQL), NoSQL (e.g. Cassandra), distributed processing (e.g., Spark, Ray), workflow management (e.g., Airflow, Temporal), memory management (e.g., Redis/Valkey), etc.
• 3+ years' experience contributing towards end-to-end software development lifecycles (version control, CI/CD pipelines, Kubernetes clusters, testing, monitoring & alerting, production support, etc.).
• 3+ years' experience building evaluation and observability systems for AI/ML models and LLMs, especially utilizing GPU-powered infrastructure.
• Familiarity with harness engineering concepts — memory management, RAG, context/ tool management, guardrails, etc.
• Strong communication and problem-solving skills to excel in dynamic, cross-functional decision-making environments.
• Bachelor's degree or above in Computer Science, Engineering, Statistics, or a related field.

Nice To Haves

• 3+ years' experience building conversational experiences and agentic workflows, leveraging open-source and proprietary LLMs
• Experience contributing to AI agent harness infrastructure — tool dispatch, error recovery, session state management, or sub-agent coordination using feedforward/feedback control patterns.
• Experience with AI agent skill systems — building or integrating reusable skill packages, skill registries, MCP servers, etc. along with governance & control measures.
• Experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI).
• Experience with LLM observability platforms such as LangSmith, Langfuse, etc.
• Experience building ai agent guardrails

Responsibilities

• Contribute to building an enterprise AI agent skill ecosystem — developing services that support authoring, publishing, discovering, and versioning reusable skill packages (SKILL.md standard).
• Implement skill marketplace features including search/discovery, security vetting pipelines, and progressive disclosure loading.
• Build and maintain AI agent harness components — the non-model infrastructure (tool dispatch, context management, error recovery, session state) that makes AI agents reliable for long-running workflows.
• Implement feedforward guides and feedback sensors mixing computational and inferential controls.
• Contribute to context engineering systems that manage the LLM context window — memory management, RAG pipelines, context compaction/summarization, scratchpads, and dynamic skill/tool loading — ensuring AI agents receive the right information at the right time.
• Implement guardrail components including input validation, prompt injection defense, PII detection, output verification, and skill-level security scanning.
• Contribute to bounded autonomy systems, human-in-the-loop escalation paths, and audit trail infrastructure.
• Contribute to experimentation of software platforms, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
• Collaborate with cross-functional teams including data scientists, ML engineers, software engineers, product managers, and designers to gather requirements, define project scope, and prioritize feature backlogs for AI agent use cases.
• Assist in the planning and estimation of software development projects, ensuring efficient allocation of resources and timely delivery of solutions.
• Mentor and guide junior engineers via code reviews and design sessions, fostering a collaborative and high-performance team culture, elevating AI engineering best practices across the company.

Benefits

• 401K savings plan vested from day one that offers a 6% match
• performance and recognition-based incentives
• tuition assistance
• mental healthcare
• fertility and adoption assistance
• workplace flexibility
• GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

What This Job Offers

• Job Type: Full-time
• Career Level: Senior