Staff Engineer

GEICO•Bethesda, MD

7d•$115,000 - $230,000

About The Position

GEICO is seeking a Staff Engineer to help shape the multi-channel communications infrastructure that connects claims adjusters with customers—letters, email, SMS, Push Notifications and fax—throughout the claims journey. This is a senior, hands-on individual contributor role for someone with deep Java and cloud-native expertise, fluency in AI-assisted software development, strong collaboration skills, and a proven ability to deliver scalable, resilient, production-ready systems. You will partner with engineering teams, product leaders, UX, and business stakeholders to design, build, and scale platforms that automate communication workflows, generate compliant correspondence at volume, and elevate customer and adjuster experiences. You will also mentor engineers across the team—including coaching others on effective use of AI coding assistants—fostering a culture of technical excellence, operational ownership, and continuous learning. About the Team Join Claims Platform Engineering – Communications (Claims Tech Sentries). We own the systems that deliver the right message to the right person at the right time across letters, email, SMS, and fax. Our portfolio spans event-driven orchestration rules (CORE), email, SMS, Push and fax channels, document authoring and letter generation, and modernization of legacy notification paths onto a unified platform. Strategic Work You Will Influence Next-Gen Communications Rules Engine (CORE): Configuration-based, event-driven rules that decide when and how to communicate across the claims lifecycle—workflow orchestration, rule evaluation, and platforms that let business users shape complex logic. Document Authoring & Letter Generation: Intelligent document systems that produce personalized, compliant correspondence at scale, including template authoring and orchestration with enterprise document platforms. Channel Delivery & Modernization: Cloud-native services for outbound email, SMS, and fax, plus modernization of multi-channel notification paths onto unified platform services. Gen AI–Powered Communications: Applied generative AI for personalized messaging across text, email, and letters—with attention to tone, compliance, and customer experience.

Requirements

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.

Nice To Haves

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).

Responsibilities

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.