Senior Staff Engineer, Java / Test Engineering & Applied AI

GEICO

Confirmed live yesterday High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Bethesda, MD
Salary: $130,000–$260,000 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $190k

This role $195k

$114k $276k

below market most similar roles pay here above market

This role pays more than 59% of similar roles. Most pay $157,150–$222,000 — the blue band above. At the midpoint, this role pays about $195k versus about $190k for comparable roles.

Based on 240 similar postings.

Employer

About GEICO

GEICO (Government Employees Insurance Company) is one of the largest auto insurers in the United States, offering affordable auto, home, renters, and other personal insurance products. Industry: Insurance

GEICO currently has 98 open roles on FindRole.

Listed pay typically runs $110,000–$230,000 across 96 roles with salary data.

Most-posted roles

View all roles at GEICO

At a glance

TL;DR · Senior Staff Engineer, Java / Test Engineering & Applied AI

Role Posting Log in to save

The Senior Staff Engineer - Java / Test Engineering & Applied AI - Hybrid works within the engineering organization to innovate, build, and enhance large-scale systems. This role involves setting the technical direction for medium-to-large product or platform capabilities, leading multi-team technical roadmaps, and defining reusable frameworks and standards. Key responsibilities include driving the adoption of intelligent automation, managing automated testing strategies across the test pyramid, and integrating AI-augmented workflows into enterprise solutions. The position requires deep expertise in Java, C#, Python, SQL, NoSQL, GraphQL, gRPC, and Kafka, alongside container orchestration using Docker and Kubernetes across AWS, GCP, and Azure. The role specifically addresses the business problem of incorporating generative AI, RAG, and agentic workflows into production environments while ensuring reliability, security, and high-quality software delivery.

What does a Engineer earn in Maryland?

Median $167500 from 30 postings across 3 companies.

See salary data

Skills

Applied AI Generative AI LLM RAG Python Java C# Go Kubernetes Docker AWS GCP Azure Kafka GraphQL gRPC SQL NoSQL Microservices OAuth SAML Active Directory Temporal Fable Automated Testing

What you'll do

Own the technical architecture and direction for a medium-to-large, cross-functional product or platform capability area.
Lead the strategy and execution of a multi-team technical roadmap to increase delivery velocity and engineering capabilities.
Incorporate applied AI and intelligent automation into enterprise solutions to improve business outcomes.
Define reusable frameworks and standards while driving adoption and organizational buy-in across multiple teams.
Translate complex technical strategies into clear communications for both technical and business stakeholders.
Develop and advance automated testing strategies across the entire test pyramid, including unit, integration, and performance tests.
Accelerate test creation and maintenance using AI-assisted generation, coverage gap analysis, and failure clustering.
Coach Staff and Senior engineers on architecture, decision-making, and stakeholder communication to multiply leadership capacity.

What we're looking for

Bachelor’s degree in Computer Science, Information Systems, or equivalent education or work experience.
10+ years of full-stack development experience using Java, C#, Python, or Go.
6+ years of experience with architecture and technical direction across multiple teams.
4+ years of experience with AWS, GCP, Azure, or another cloud service provider.
2+ years of experience shipping LLM, generative AI, or intelligent automation in production.
Extensive experience architecting large-scale SaaS platforms and microservices using GraphQL, gRPC, Kafka, and container orchestration.
Deep expertise in automated testing practices across the test pyramid, including shift-left quality and CI gates.
Significant ownership of automated testing strategy with evidence of AI-assisted testing or test-platform acceleration (preferred).

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