Senior Machine Learning Engineer, AI Agent Platform

About the role

GEICO is seeking an experienced Senior Machine Learning Engineer to join its AI organization. The role involves developing GEICO's virtual assistant platform, enhancing productivity for 30K+ internal associates and the customer experience for millions of policyholders. The ideal candidate will contribute to building an enterprise AI agent skill ecosystem, implementing skill marketplace features, and collaborating with cross-functional teams.

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.
• 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.

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.

Qualifications

• Bachelor's degree or above in Computer Science, Engineering, Statistics, or a related field.

Skills

• Proven track record of building high-performance Generative AI Systems and platforms.

Pay

$105,000.00 - $230,000.00 per year. 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.