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About This Role
Why Join GEICO?
At GEICO, we offer a rewarding career where your ambitions are met with endless possibilities.
Every day we honor our iconic brand by offering quality coverage to millions of customers and being there when they need us most. We thrive on relentless innovation to exceed our customers' expectations while making a real impact on local communities nationwide.
Founded in 1936, GEICO is a member of the Berkshire Hathaway family of companies and one of the largest auto insurers in the United States. When you join our company, we want you to feel valued, supported, and proud to work here. That's why we offer the GEICO Pledge: Great Company, Great Culture, Great Rewards, and Great Careers.
GEICO is seeking a highly experienced Senior Staff Security Engineer to lead the strategy and technical execution of Vulnerability Management and Offensive Security across a complex, hybrid technology ecosystem. This role blends deep security engineering expertise with strong architectural leadership, hands\-on experience, leveraging frontier AI models for security, drive customer success, and provide advisory to senior executive leaders.
This is a high‑impact hands\-on technical role who maintains a strong connection with both customers and underlying systems for shaping the company’s vulnerability management maturity, influencing engineering culture, and safeguarding critical systems. The Senior Staff Security Engineer will drive meaningful, measurable improvements to security posture while enabling teams to build and ship technology with confidence. They drive customer success for the vulnerability management and offensive security functions. They demonstrate a keen ability to dive deep into complex problems to fully understand how systems operate, discerning when to make incremental improvements and when to challenge the status quo to drive impactful results. They are well\-versed with Vulnerability Management Lifecycle \- asset discovery, internal/external scans, contextualization and risk\-based assessment, triaging of CVEs, detection authoring, security data pipeline, reporting, and remediation.
This role is an advisor to executive leaders and is critical to our cybersecurity objectives. The position requires a strong security and engineering background with hands\-on experience. The successful candidate will play a key role in maintaining a strong security posture for the company through close collaboration with infrastructure, development, product, and other organizations across GEICO to integrate security into the ecosystem from design through deployment to sustainable operations.
At GEICO’s Cybersecurity organization, we are committed to strengthening the company’s digital resilience and advancing the security of our technology ecosystem. Our mission is to proactively protect our customers, associates, and business by modernizing our security capabilities, elevating our defensive posture, and enabling secure innovation at scale. As GEICO transforms its technology landscape, Cybersecurity plays a pivotal role in delivering secure, reliable, and future‑ready solutions that support every line of business and every customer channel—empowering the enterprise with protection that is adaptable, intelligent, and built for the evolving threat landscape.
What do you bring in?
This role is designed for a highly technical, hands\-on security engineer who thrives at the intersection of vulnerability management, offensive security, and emerging AI\-driven threats and defenses. You bring deep domain expertise across penetration testing, red and purple teaming, and modern security engineering, coupled with the ability to leverage AI to scale both offensive insights and defensive capabilities. You are customer\-obsessed in your approach to security, operating with a strong sense of ownership and urgency in a fast\-paced environment. You excel at translating complex technical risks and security concepts into clear, business\-aligned outcomes that resonate with senior executives and drive action. A self\-starter by nature, you navigate ambiguity with confidence, independently overcome challenges, and consistently deliver measurable results. You are equally comfortable advising executive leadership as you are designing and building secure systems, bringing a rare blend of strategic influence and deep engineering execution to elevate the organization’s security posture.
Key Responsibilities
VM \& OffSec Execution
- Lead the strategy and technical execution of Vulnerability Management, Offensive Security, and AI\-augmented security at scale.
- Lead the full vulnerability lifecycle: discovery, validation, risk analysis, prioritization, and remediation measurement.
- Leverage business contextualization, underlying systems, threat intelligence, and AI frontier models to perform risk assessment for identifying true risk to drive remediation.
- Integrations among scanning tools, asset inventory, CMDBs, ticketing, CI/CD, and monitoring pipelines to streamline workflows.
- Evaluate, test, and implement emerging AI technologies that advance automated discovery and remediation.
- Design automation to reduce manual work, increase accuracy, and accelerate remediation.
- Generate data‑driven insights that help teams understand, prioritize, and resolve vulnerabilities efficiently.
Cross‑Functional Partnership
- Drive customer success for the vulnerability management and offensive security functions.
- Play role of an advisor to senior executive leadership.
- Collaborate with cloud, infrastructure, DevOps, and product engineering groups to integrate vulnerability management into pipelines and delivery workflows.
- Work closely with risk, compliance, governance, and incident response teams to ensure alignment with organizational and regulatory standards.
- Communicate vulnerability trends, risk implications, and remediation strategies to technical and non‑technical stakeholders.
Operational Excellence \& Measurement
- Define KPIs, SLAs, dashboards, and reporting models to drive accountability and measurable vulnerability reduction.
- Establish repeatable processes, playbooks, and workflows that ensure consistent VM operations across teams and environments.
- Ensure the reliability, performance, and scalability of VM tools and data pipelines.
Leadership, Mentoring \& Team Development
- Mentor junior and mid‑level engineers, offering guidance on advanced security concepts, engineering best practices, and career development.
- Serve as a multiplier by elevating skillsets across teams through coaching, pairing, design reviews, and knowledge‑sharing.
- Influence architecture and engineering leadership with clear communication, strong decision‑making, and the ability to simplify complex security issues.
Required Qualifications
- 10\+ years of experience in cybersecurity or security engineering roles.
- Deep expertise with vulnerability management tools, methodologies, and industry standards.
- Hands‑on experience with modern infrastructure, cloud services (AWS/Azure/GCP), container platforms, and operating systems.
- Proficiency with a modern programming language (Python, Go, Java, etc.) and scripting for automation at scale.
- Strong understanding of security architecture, networking, operating systems, identity, and cloud services.
- Proven ability to lead, mentor, and inspire engineers across multiple teams.
- Strong communication skills with the ability to influence senior stakeholders and translate complex risks into actionable guidance.
- Hands\-on experience implementing cybersecurity frameworks e.g. NIST CSF
- Hands\-on experience with leading compliance initiatives to meet e.g. PCI, SOX, NYDFS, etc.
Preferred Qualifications
- Exposure to comprehensive security assessment, penetration testing, threat modeling, or security research.
- Familiarity with SIEM, SOAR, and asset intelligence integrations.
- Security certifications (CISSP, GCSA, OSCP, cloud security certs) are a plus.
- Experience embedding security controls into CI/CD pipelines and DevSecOps workflows.
Education:
- Bachelor’s degree in computer science, Cyber Security, or equivalent education with relevant work experience
Annual Salary
$120,000\.00 \- $260,000\.00
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.
At this time, GEICO will not sponsor a new applicant for employment authorization for this position. 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.
Salary Context
This $120K-$260K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 2130 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,133 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At GEICO, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $185,000 based on 13,200 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. Disclosed range: $120K to $260K.
Across all AI roles, the market median is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Safety ($274,200) and AI Engineering Manager ($268,700). By seniority level: Entry: $97,760; Mid: $165,778; Senior: $227,400; Director: $250,000; VP: $250,000.
GEICO AI Hiring
GEICO has 12 open AI roles right now. They're hiring across AI/ML Engineer, AI Agent Developer. Positions span Palo Alto, CA, US, New York, NY, US, Dallas, TX, US. Compensation range: $115K - $350K.
Location Context
Across all AI roles, 14% (583 positions) offer remote work, while 3,532 require on-site attendance. Top AI hiring metros: New York (2,760 roles, $211,000 median); San Francisco (2,258 roles, $253,000 median); Los Angeles (1,841 roles, $195,000 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,133 open positions tracked in our dataset. By seniority: 106 entry-level, 1,901 mid-level, 1,663 senior, and 463 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (583 positions). The remaining 3,532 roles require on-site or hybrid attendance.
The market median for AI roles is $200,700. Top-quartile compensation starts at $254,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Safety ($274,200 median, 57 roles); AI Engineering Manager ($268,700 median, 42 roles); Research Engineer ($260,000 median, 442 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,133 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,865), Data Scientist (339), AI Software Engineer (313). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (106) are outnumbered by mid-level (1,901) and senior (1,663) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 463 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (583 positions), with 3,532 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $200,700. Top-quartile roles start at $254,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $274,200 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,128 postings), Aws (1,324 postings), Azure (1,003 postings), Rag (916 postings), Gcp (817 postings), Pytorch (655 postings), Prompt Engineering (639 postings), Claude (571 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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