Staff Engineer

- Provide technical architecture and leadership within the team and across multiple projects spanning orchestration, channel delivery, and document platforms.

- Architect, build, and deploy cloud systems that meet high standards for scalability, resilience, performance, security, and availability.

- Lead design of event-driven and orchestration-heavy workflows, including rule evaluation, asynchronous processing, and integration across Claims services.

- Build RESTful APIs and microservices with deep consideration for distributed systems, reliability, observability, and compliance.

- Develop and maintain internal web applications that support engineering and business tooling needs.

- Establish and model engineering best practices for reliability, testing, deployment, rollback, monitoring, and operational readiness.

- Integrate comprehensive observability—metrics, distributed tracing, structured logging, and alerting—and lead post-incident reviews that drive systemic improvement.

- Collaborate with product, engineering, operations, and business partners to translate needs into technical designs and deliver measurable outcomes.

- Use AI coding assistants daily (e.g., GitHub Copilot, Cursor, or Claude) to accelerate design, implementation, testing, and refactoring—while applying strong engineering judgment to review, validate, and own the resulting code.

- Champion AI-assisted software development across the team: establish effective prompts and workflows, coach engineers on productive use, and set standards for quality, security, and accountability when shipping AI-assisted work.

- Mentor engineers through coaching, pairing, reviews, and architectural guidance; raise the bar on design quality and decision-making.

- Lead through technical influence by guiding architecture, experimentation, and delivery across initiatives that span multiple teams.

- Drive innovation thoughtfully—including modern Java, cloud-native patterns, and advancing how the team builds with AI assistance—while keeping production excellence first.

- 8 or more years of professional software engineering experience, including 2 or more years in a technical leadership capacity (architecture, multi-project leadership, or equivalent influence).

- Deep expertise in Java (Java 17+; Java 21 preferred) and the Spring Boot 3.x ecosystem.

- Demonstrated proficiency with AI-assisted software development using tools such as GitHub Copilot, Cursor, or comparable AI coding assistants—including integrating them into day-to-day requirements analysis, design, coding, testing, documentation and issue support practices.

- Experience helping teams adopt AI coding assistants thoughtfully, with clear expectations for code quality, security, and engineer ownership of AI-generated output.

- Proven experience building scalable, resilient, secure, and maintainable products and systems that run reliably in production.

- Expert knowledge of microservices, distributed systems, and cloud-native architecture (Azure, AWS or GCP).

- Strong competency in service design, performance optimization, reliability engineering, and observability / SRE practices.

- Experience building RESTful APIs and web applications (HTML, CSS, JavaScript), with willingness to work with frontend technologies as needed for internal tools.

- Track record of improving system reliability and scalability through architectural improvements, performance optimization, and operational enhancements.

- Ability to collaborate deeply across teams and co-create solutions with engineers, product managers, and domain experts.

- Experience mentoring engineers and elevating team capabilities through reviews, guidance, and standards.

- Excellent communication skills, including the ability to influence technical direction and explain complex topics to senior leadership and non-technical stakeholders.

- A history of delivering measurable business outcomes from complex technical initiatives.

- Experience with event-driven architectures and workflow orchestration (e.g., Kafka, Temporal, or similar).

- Reactive programming, asynchronous systems, and high-throughput messaging patterns.

- Background in Site Reliability Engineering (SRE) or platform engineering.

- Deep expertise in distributed tracing, log aggregation, and alerting systems.

- Experience defining team playbooks or standards for AI-assisted development (prompt patterns, review checklists, security guardrails).

- Experience with A/B testing, feature flags, and data-driven development.

- Track record of successful system migrations, large-scale refactoring, or legacy modernization.

- Experience with insurance, financial services, or other regulated industries.

- Contributions to open-source projects or technical thought leadership.

- Familiarity with document generation, communications platforms, or multi-channel notification systems.

- Exposure to applied Gen AI in production workflows (personalization, document intelligence, or assistant-style experiences).

- A collaborative engineer who works well with cross-functional partners and supports the growth of those around you.

- A hands-on builder who ships reliable, scalable, production-grade systems rather than stopping at proof of concept.

- An AI-fluent engineer who treats coding assistants as a force multiplier—and never as a substitute for sound design, rigorous review, and personal accountability for production code.

- Someone who understands how to design systems that scale smoothly, recover gracefully, and operate reliably under load.

- A systems thinker who connects APIs, events, orchestration, and observability into cohesive platforms.

- A natural mentor who enjoys helping others grow in architecture, Java/cloud-native engineering, AI-assisted workflows, and operational excellence.

- An innovative thinker who explores new approaches and applies them thoughtfully to real-world Claims problems.

- Driven by real-world impact, customer and adjuster value, and long-term engineering excellence.

Annual Salary

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.

The GEICO Pledge:

Great Company: Protecting customers through life’s twists and turns with innovation and integrity.

Great Careers: Personalized development programs, mentorship, and certification assistance.

Great Culture: Inclusive and collaborative culture rooted in shared success.

Great Rewards: Competitive pay, benefits, and flexibility to support your well-being and future.

The equal employment opportunity policy of the GEICO Companies provides for a fair and equal employment opportunity for all associates and job applicants regardless of race, color, religious creed, national origin, ancestry, age, gender, pregnancy, sexual orientation, gender identity, marital status, familial status, disability or genetic information, in compliance with applicable federal, state and local law. GEICO hires and promotes individuals solely on the basis of their qualifications for the job to be filled.

GEICO reasonably accommodates qualified individuals with disabilities to enable them to receive equal employment opportunity and/or perform the essential functions of the job, unless the accommodation would impose an undue hardship to the Company. This applies to all applicants and associates. GEICO also provides a work environment in which each associate is able to be productive and work to the best of their ability. We do not condone or tolerate an atmosphere of intimidation or harassment. We expect and require the cooperation of all associates in maintaining an atmosphere free from discrimination and harassment with mutual respect by and for all associates and applicants.