Senior Staff ML Engineer
Overview
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.
Responsibilities
Own end-to-end design, development, and maintenance of high-performance AI solutions that use agentic workflows to deliver concrete business value for internal stakeholders and customer-facing applications.
Examples include AI agent orchestration, conversational AI solutions, knowledge assistants, process assistance and automation, 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 development.
Establish pragmatic technical visions and roadmaps that balance business outcomes, product release timelines, and engineering excellence.
Integrate and build solutions using GEICO’s AI platform architecture.
Partner with platform teams to communicate requirements, understand current capabilities and gaps, and contribute to platform feature roadmaps and development.
Ideate, define, and build first-of-its-kind solutions within GEICO, with a deep understanding of business and technical processes, applications, and architecture to guide development.
Drive the selection, evaluation, and implementation of software technologies, tools, and frameworks, balancing build vs. buy, speed to market, maintainability, etc.
Take ownership in project planning and stakeholder management, driving technical alignment, ensuring efficient resource allocation, and timely delivery of solutions.
Mentor and guide junior engineers via code reviews and design sessions, establish and enforce best practices, and foster a collaborative and high-performance team culture.
Qualifications
8+ years of experience designing and building scalable production AI/ML applications and systems in cloud environments.
5+ years owning end-to-end development, monitoring, maintenance, and continuous improvement of scalable, robust AI/ML applications.
5+ years of experience with training, finetuning, real-time/batch inferencing, and evaluation systems for AI/ML models and LLMs used in production systems.
5+ years of experience managing the end-to-end software development life cycle (e.g. CI/CD pipelines, Kubernetes-based deployments, testing, monitoring & alerting, production support etc.) for Generative AI applications, backend systems, and APIs.
Experience using frameworks to build LLM-based agentic workflows such LangSmith/LangGraph or similar.
Experience using typical agentic communication standards such as A2A, MCP, and similar to design, architect, and build working multi-agent applications.
Proficient in Python, Java or similar general-purpose programming languages.
Bonus Qualifications
5+ years interfacing directly with internal business stakeholders and/or external stakeholders on AI/ML initiatives.
Extensive experience using cloud provider solutions such as Azure and AWS to deploy and maintain AI/ML products.
Extensive experience using tools that power production-grade LLM-based AI agents, such as eval frameworks, agent tooling, RAG pipelines, prompt engineering, etc.
Experience building products with LLM-based AI agent workflows via both no code/low code and traditional high-code development environments.
Experience with agentic workflows to solve problems in the insurance domain.
Strong communication and problem-solving skills to excel in dynamic, cross-functional and ambiguous decision-making environments.
Pay
Annual Salary: $150,000.00 - $300,000.00
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.