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About This Role
If you’re passionate about being part of a dynamic organization that enables a Fortune 100 company with nearly $70 billion in annual sales to drive innovation and adopt new technologies that deliver business results, then Nationwide’s Technology team could be the place for you! At Nationwide®, “on your side” goes beyond just words. Our customers are at the center of everything we do and we’re looking for associates who are passionate about delivering extraordinary care.This role will work a hybrid schedule coming into the Columbus, Ohio, Des Moines, Iowa, or Scottsdale, Arizona office 2 days (Mondays \& Wednesdays) per week. Remote internal associates may also be considered.
The Cyber Security Operations Center’s Innovation and Integration (CSOC\-INI) team transforms emerging ideas into secure, production\-ready capabilities that advance cyber defense. Across agentic solutions, modern application engineering, platform foundations, and security data engineering, we translate complex operational needs into scalable, observable outcomes.
This is a high\-impact opportunity to build the secure production backbone for agentic AI in Cyber Security Operations. In this role, you’ll create and operate the platform capabilities that let agentic solutions run safely and reliably at enterprise scale—from cloud environments, deployment pipelines, and runtime controls to identity, observability, and recovery mechanisms. You’ll partner closely with solution engineers and cyber security leaders to make sure innovative AI services are not just deployable, but governable, resilient, and ready for real\-world operations.
Job description
Builds and operates the secure platform foundation that hosts agentic solutions in production for the Cyber Security Operations Center.
Owns environments, deployment automation, runtime controls, identity and access patterns, observability, operational readiness, and service reliability.
Partners closely with agentic solution engineers to provide reusable platform capabilities and to ensure agentic services canbe deployed, monitored, governed, and recovered safely at enterprise scale.
Requirements
- Strong cloud and platform engineering skills
- Experience with infrastructure as code (AWS CDK), CI/CD (GitHub Actions/Harness NextGen), artifact management, and runtime hosting
- Strong knowledge of identity, access control, secrets handling, and service\-to\-service security
- Experience with observability stacks including logs, metrics, traces, and alerting
- Experience with release controls, rollback patterns, and incident response
- Working knowledge of container/image lifecycle, policy enforcement, and software supply chain security
- Familiarity with AI/agent workloads, especially their runtime, cost, and monitoring concerns
- Ability to standardize platform patterns that can be reused across multiple solutions
- Excellent verbal and written communication skills
- Security Operations experience preferred
Expectations
- Provision and maintain secure, repeatable runtime environments for agentic solutions
- Own deployment pipelines, release guardrails, and artifact promotion practices
- Implement and operate observability, alerting, health checks, and operational dashboards
- Enforce identity, access, policy, and runtime security controls
- Support feature flagging, kill\-switch patterns, rollback, and safe recovery mechanisms
- Monitor cost, performance, reliability, and capacity for production services
- Lead incident response for platform or runtime issues and partner on joint triage for solution issues
- Continuously improve platform standards, reusable capabilities, and operational maturity
\#LI\-AC1
Job Description Summary
If you’re enthusiastic about delivering secure technology solutions to support a company providing extraordinary care to its customers, then Nationwide Technology is the place for you. Nationwide's industry\-leading technology workforce embraces an agile work environment and a collaborative culture to deliver outstanding solutions and results. If that sounds like something you aspire to, we want to hear from you!
As a Cyber Operations professional, you'll be on the front line, protecting Nationwide's members and data! You will be immersed with incident response, cyber strategy and guidance, defense optimization and scanning and exploitation. We'll count on you to provide enterprise services in forensic investigation, attack and penetration, vulnerability scanning and response, cyber defense, security intelligence, security operations and infrastructure risk management.Job Description
Key Responsibilities:
- Responds to cyber incidents using industry recognized methodology, e.g., PICERL (Preparation, Identification, Containment, Eradication, Recovery and Lessons Learned).
- Creates uplift of cyber security detection and alerts for ongoing prevention of threats.
- Applies secure software and systems engineering practices throughout the delivery lifecycle to ensure our data and technology solutions are protected from threats and vulnerabilities.
- Implements automation and orchestration for the enrichment and handling of cyber security events.
- Supports vulnerability management via tools and processes and proactively identify vulnerabilities in the environment.
- Assists in the planning and execution of team activities to enrich detection and prevention controls.
- Participates in proactive cyber activity (purple teaming, threat hunting, red teaming, etc.) and expands awareness across all aspects of the MITRE ATT\&CK framework.
- Identifies critical log sources and system events used for creation and tuning of cyber security detections.
- Maintains awareness of the cyber threat landscape to assist with the evaluation, enrichment and dissemination for action to protect Nationwide members and environment.
May perform other responsibilities as assigned.
Reporting Relationships: Reports to Manager, Risk Leader or above.
Typical Skills and Experiences:
Education: Undergraduate studies in cyber security, management information systems, engineering, math, computer science, data analytics or comparable experience and education strongly preferred. Graduate studies in cyber security, computer science or a related field are a plus.
License/Certification/Designation: Preferred certifications include: Certified Information Systems Security Professional (CISSP), Cisco Certified Network Associate (CCNA), Certified Ethical Hacker (CEH), GIAC Certified Intrusion Handler (GCIH), Digital Forensics Investigation: EnCase Certified Examiner (EnCE) certification, GIAC Strategic Planning Policy and Leadership (GSTRT), GIAC Security Expert (GSE), Certified Cloud Security Professional (CCSP), AWS Certified Cloud Practitioner, AZ500\.
Experience: At least three years of experience in technology. Experience in working with operating systems, networking, desktop support, application development, end point security, database management or information security. Successful candidates will have experience configuring and using Windows and Linux/Unix operating systems.
Knowledge, Abilities and Skills:Action oriented and ability to make decisions and recommendations. Aptitude to build partnerships, understand business processes, and set priorities. Solid communication skills. Insurance and/or financial services industry knowledge a plus.
Other criteria, including leadership skills, competencies and experiences may take precedence.
Staffing exceptions to the above must be approved by the hiring manager’s leader and Human Resource Business Partner.
Values: Regularly and consistently demonstrates Nationwide Values.
Job Conditions:
Overtime Eligibility: Exempt (Not Eligible)
Working Conditions: Hybrid to normal office environment.
ADA: The above statements cover what are generally believed to be principal and essential functions of this job. Specific circumstances may allow or require some people assigned to the job to perform a somewhat different combination of duties.
We currently anticipate accepting applications until 08/21/2026\. However, we encourage early submissions, as the posting may close sooner if a strong candidate slate is identified before the deadline.Benefits
We have an array of benefits to fit your needs, including: medical/dental/vision, life insurance, short and long term disability coverage, paid time off with newly hired associates receiving a minimum of 18 days paid time off each full calendar year pro\-rated quarterly based on hire date, nine paid holidays, 8 hours of Lifetime paid time off, 8 hours of Unity Day paid time off, 401(k) with company match, company\-paid pension plan, business casual attire, and more.
Nationwide is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive culture where everyone feels challenged, appreciated, respected and engaged. Nationwide prohibits discrimination and harassment and affords equal employment opportunities to employees and applicants without regard to any characteristic (or classification) protected by applicable law.
This position could be filled within any of the lower 48 U.S. states.
Smoke\-Free Iowa Statement: Nationwide Mutual Insurance Company, its affiliates and subsidiaries comply with the Iowa Smokefree Air Act. Smoking is prohibited in all enclosed areas on or around company premises as well as company issued vehicles. The company offers designated smoking areas in which smoking is permitted at each individual location. The Act prohibits retaliation for reporting complaints or violations. For more information on the Iowa Smokefree Air Act, individuals may contact the Smokefree Air Act Helpline at 888\-944\-2247\.
For NY residents please review the following state law information: Notice of Employee Rights, Protections, and Obligations LS740 (ny.gov) https://dol.ny.gov/system/files/documents/2022/02/ls740\_1\.pdfNOTE TO EMPLOYMENT AGENCIES:
We value the partnerships we have built with our preferred vendors. Nationwide does not accept unsolicited resumes from employment agencies. All resumes submitted by employment agencies directly to any Nationwide employee or hiring manager in any form without a signed Nationwide Client Services Agreement on file and search engagement for that position will be deemed unsolicited in nature. No fee will be paid in the event the candidate is subsequently hired as a result of the referral or through other means.
Nationwide pays on a geographic\-specific salary structure and placement within the actual starting salary range for this position will be determined by a number of factors including the skills, education, training, credentials and experience of the candidate; the scope, complexity and location of the role as well as the cost of labor in the market; and other conditions of employment. If a Sales job, Sales Incentives, based on performance goals are possible in addition to this range. Note on Compensation for Part\-Time Roles: Please be aware that the salary ranges listed below reflect full\-time compensation. Actual compensation may be prorated based on the number of hours worked relative to a full\-time schedule.
The national salary range for Specialist, Cyber Operations Professional : $95,500\.00\-$177,500\.00
The expected starting salary range for Specialist, Cyber Operations Professional : $95,500\.00 \- $143,500\.00
- Job Category Technology
- Position Type Full Time
- Posted 2026\-08\-13T07:08:00\.970907\+00:00
- Location(s)
+ Ohio \- Columbus, Three Nationwide Plaza
+ United States \- Remote
+ Iowa \- Des Moines, 1100 Locust Street
+ Arizona \- Scottsdale, 18700 North Hayden Road
- Line of Business
- Entity
- Recruiter
- Hiring Manager
- Experience Level
- Req ID 099563
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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Nationwide Mutual Insurance Company, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Nationwide Mutual Insurance Company AI Hiring
Nationwide Mutual Insurance Company has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Columbus, OH, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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