Senior Machine Learning Engineer, AI Agent Platform
Geico· enterprise· Insurance· Jun 5, 2026 · 5mo agoPosted 144 days ago
New York City, NY
In office
Full-time
Senior
$105K–$230K
5+ years exp
Before you apply
Ghost Signal:
Open since June 5, 2026 — 144 days, and still accepting applications.
Job description
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.
Senior Machine Learning Engineer – AI Agent Platform
Position Description 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.
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.
Basic Qualifications 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.
Preferred Qualifications 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
Annual Salary
$105,000.00 - $230,000.00 The above annual salary range is a general guideline. Multiple factors are taken into consideration to arrive at the final hourly rate/ annual salary to be offered to the selected candidate. Factors include, but are not limited to, the scope and responsibilities of the role, the selected candidate’s work experience, education and training, the work location as well as market and business considerations.
GEICO will consider sponsoring a new qualified applicant for employment authorization for this position.
The GEICO Pledge:
Great Company: Protecting customers through life’s twists and turns with innovation and integrity.
Great Careers: Personalized development programs, mentorship, and certification assistance.
Great Culture: Inclusive and collaborative culture rooted in shared success.
Great Rewards: Competitive pay, benefits, and flexibility to support your well-being and future.
The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.
GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.
Application prep
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Keywords to mirror
machine learningaimlllmjavapythonci/cdkubernetes
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