Staff Software Engineer – Java, Spring Boot & AI Microservices

GEICO; Bethesda (MD); On-site; USD 115,000 - 230,000; Full time

Job summary

GEICO is seeking a Staff Software Engineer to lead the design and delivery of microservice-based architectures using Java and Spring Boot, with a focus on Generative AI capabilities.

The role includes mentoring engineers, collaborating with Enterprise Architects, Product Managers, and ML teams to drive AI initiatives, and advancing observability and DevOps practices in a fast-paced environment.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 10+ years of professional Java software engineering experience.
• Deep knowledge of Java 21 and Spring Boot 3.4.x+.
• Experience with distributed systems and microservices.
• Hands-on with Generative AI and RAG concepts.
• Experience with AI-assisted development tools (Claude, Cursor, Codex, etc.).
• Strong RESTful API design and cloud/DevOps practices.

Responsibilities

• Design, develop, and maintain scalable microservices using Java and Spring Boot.
• Define technical roadmaps with architects and product managers.
• Build AI-powered features and Generative AI use cases.
• Collaborate with ML/Data Science teams on AI models.
• Provide technical leadership and code quality practices.
• Mentor engineers and foster an inclusive team environment.
• Drive observability, automation, and engineering process improvements.

Skills

Java 21+

Spring Boot 3.4.x

Microservices

RESTful APIs

Cloud (AWS/Azure/GCP)

CI/CD

Observability

Mentoring

Generative AI

Education

Bachelor's or Master's in CS/Engineering

Tools

Docker

Kubernetes

Spring Cloud

Claude/Codex Cursor

Job description

GEICO is seeking a Staff Software Engineer to lead the design and delivery of microservice-based architectures using Java and Spring Boot, with a focus on Generative AI capabilities.

The role includes mentoring engineers, collaborating with Enterprise Architects, Product Managers, and ML teams to drive AI initiatives, and advancing observability and DevOps practices in a fast-paced environment.