Director of Engineering, AI Infrastructure

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.

About the Role:

We are seeking a visionary and execution-focused Director of Engineering, AI Infrastructure to lead GEICO’s AI/ML infrastructure initiatives as part of our mission to become an AI-native insurer. This role will be pivotal in architecting, scaling, and operationalizing the foundational AI/ML platforms and services that power the next generation of intelligent insurance products.

As the Director, you will lead a multidisciplinary engineering organization focused on delivering scalable compute infrastructure, model observability, LLM platforms, distributed training systems, and secure ML services. You will work closely with data scientists, ML engineers, product teams, and enterprise stakeholders to ensure our AI stack enables rapid experimentation, robust deployment, and efficient governance at scale.

Key Responsibilities:

• Lead and scale the AI Infrastructure engineering team, fostering technical excellence, innovation, and operational rigor.

• Define and execute the strategic roadmap for GEICO’s AI infrastructure, ensuring alignment with business goals and AI/ML platform needs.

• Oversee delivery of core infrastructure components, including:

  • GPU and distributed training platforms (e.g., AnyScale/Ray)

  • LLM inference and fine-tuning platforms (OpenAI, Fireworks, in-house)

  • Feature store and real-time data pipelines

  • ML observability and monitoring systems

• Drive MLOps best practices across model development, CI/CD, performance tracking, and governance.

• Ensure infrastructure scalability, reliability, and compliance with internal and external security/privacy standards.

• Collaborate with research and innovation teams on advanced initiatives like quantum ML and confidential AI.

• Lead cross-cutting programs including cost optimization, model lifecycle management (Model Hive), and standardized model development (MDLC).

• Mentor senior engineering leaders and establish a high-performing, inclusive team culture.

• Influence enterprise-wide architectural decisions and represent the AI Infra organization across technical forums.

Minimum Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.

• 10+ years of experience in software or infrastructure engineering, with 5+ years in technical leadership roles.

• Proven experience building and scaling AI/ML infrastructure, including GPU clusters, distributed training, and real-time model serving.

• Expertise with AI/ML frameworks (e.g., PyTorch, TensorFlow) and orchestration tools (e.g., Ray, Kubernetes, Docker).

• Strong grasp of MLOps, data governance, and ML observability best practices.

• Deep familiarity with cloud platforms (AWS, GCP, or Azure) and modern CI/CD practices.

• Experience leading cross-functional engineering teams and managing technical delivery at scale.

Preferred Qualifications:

• Experience with LLMs (e.g., OpenAI, Fireworks) and advanced techniques such as RAG and agent-based orchestration.

• Knowledge of privacy-preserving AI, including federated learning and differential privacy.

• Familiarity with semantic data models, streaming feature stores, and confidential computing.

• Exposure to quantum computing concepts applied to ML workloads.

• Strong executive presence, with the ability to influence technical and non-technical stakeholders.

• Contributions to open-source projects, patents, or technical publications in the AI infrastructure space.

What We Offer:

• Opportunity to shape the AI infrastructure of a Fortune 100 company undergoing AI transformation.

• A collaborative, mission-driven culture that values innovation and impact.

• Access to cutting-edge tools, frameworks, and research opportunities.

• Competitive compensation, equity, and benef