Senior Staff Engineer, Software Engineering (hybrid)

GEICO GEICO · Insurance · Bethesda, MD +2

Senior Staff Engineer role focused on architecting and implementing scalable infrastructure and AI-powered systems. The role involves defining technical vision, leading critical projects, and applying AI/ML to solve business problems, with a strong emphasis on infrastructure, data systems, and applied AI within an enterprise context.

What you'd actually do

  1. Define and drive the technical vision for infrastructure and AI-powered systems across the organization
  2. Design, architect, and implement highly scalable, fault-tolerant distributed systems
  3. Lead technical decision-making on critical projects, balancing short-term needs with long-term sustainability
  4. Establish and champion engineering best practices, design patterns, and coding standards
  5. Architect and optimize compute infrastructure for performance, reliability, and cost efficiency

Skills

Required

  • Deep expertise in infrastructure systems, including compute platforms (Kubernetes, Docker, cloud services), networking, and storage
  • Strong database experience across relational databases (PostgreSQL, MySQL) and NoSQL solutions (MongoDB, Cassandra, Redis, DynamoDB)
  • Demonstrated experience applying AI to solve real-world problems in production environments
  • Expert-level proficiency in at least two programming languages (e.g., Python, Java, Go, Rust)
  • Experience designing and building distributed systems at scale
  • Strong understanding of cloud platforms (Azure OR AWS) and infrastructure-as-code practices
  • Hands-on experience with CI/CD pipelines, build systems, and deployment automation (e.g., GitHub Actions, Jenkins, Azure DevOps, ArgoCD)
  • Background in building real-time data processing systems (Kafka, Flink, Spark)
  • Excellent communication skills with the ability to articulate complex technical concepts to diverse audiences
  • Experience working in a platform engineering team, building internal developer platforms or shared infrastructure services

What the JD emphasized

  • AI/ML to solve high-impact business problems
  • emerging AI technologies and evaluate their applicability

Other signals

  • Apply AI/ML to solve business problems
  • Architecting scalable infrastructure for AI-powered systems
  • Optimize compute infrastructure for AI performance