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About This Role
Description
Principal Engineer, Enterprise Browser Data Protection \& Support
Principal Engineer
Enterprise Browser Data Protection \& Support
Position Summary
Serve as the senior technical authority for the architecture, engineering, security, and operational support of enterprise browser and browser\-based data protection capabilities. Lead platform strategy, complex troubleshooting, policy design, integrations, automation, and continuous improvement across a large, regulated enterprise environment.
Key Responsibilities
- Own the enterprise browser security architecture, roadmap, standards, and lifecycle.
- Design and implement browser\-based data loss prevention controls, including download, upload, clipboard, print, screen capture, watermarking, and session restrictions.
- Integrate browser platforms with identity, endpoint management, DLP, SIEM/SOAR, secure web gateway, CASB, SASE, and zero trust technologies.
- Provide Tier 3/Tier 4 support, lead major incident response, perform root\-cause analysis, and develop operational runbooks.
- Automate deployment, policy management, monitoring, reporting, and platform health checks.
- Partner with Cybersecurity, IAM, Endpoint, Network, Cloud, Risk, Compliance, and vendor teams; mentor engineers and influence enterprise design decisions.
Required Experience
- 12\+ years in cybersecurity, infrastructure, endpoint, or platform engineering.
- 8\+ years designing and supporting enterprise security technologies.
- 5\+ years with enterprise browsers, browser isolation, secure web access, or browser\-based DLP.
- Demonstrated experience leading architecture and engineering initiatives in large, complex environments; regulated\-industry experience preferred.
Required Toolset
- Enterprise browsers/security: Island, Palo Alto Prisma Browser, Chrome Enterprise Premium, Microsoft Edge for Business, Menlo Security, or equivalent.
- Data protection: Microsoft Purview DLP, Netskope DLP, Symantec DLP, Forcepoint DLP, Digital Guardian, or equivalent.
- Endpoint/identity: Microsoft Intune, MECM/SCCM, Tanium, Jamf, Entra ID, Active Directory, Okta, CyberArk, or Ping Identity.
- Security/monitoring: Microsoft Defender XDR, CrowdStrike, Splunk, Microsoft Sentinel, Zscaler, Palo Alto, Netskope, or Cisco Secure Access.
- Automation/development: PowerShell, Python, REST APIs, Microsoft Graph, Git, Azure DevOps or GitHub; Terraform preferred.
- Strong knowledge of DNS, TLS/HTTPS, proxies, SWG, CASB, SASE, ZTNA, VPN, and cloud platforms.
Education \& Certifications
- Bachelor's degree in Computer Science, Cybersecurity, Information Technology, Engineering; master's degree preferred.
- Required: CISSP, CCSP, CISM, or a comparable advanced security certification.
- Preferred: Microsoft SC\-100, SC\-300, or SC\-400; GIAC GCED/GCIH; AWS Security \- Specialty; Azure Solutions Architect; ITIL 4; or TOGAF.
Core Competencies
- Enterprise architecture, technical leadership, strategic planning, executive communication, vendor management, risk assessment, incident leadership, mentoring, and cross\-functional collaboration.
Pay Transparency
- The salary range for this position is $150,000 to $190,000 per year, plus an opportunity to earn additional incentive earnings. Actual pay is based on various factors including, but not limited to, the budget, work location, and relevant skills and experience.
Benefits
Comprehensive benefits include medical, dental, and vision coverage, retirement plans, parental leave, flexible work arrangements, education reimbursement, wellness programs, and generous paid time off exceeding local requirements.
Citizens Benefits Overview
For an overview of our benefits, visit our Careers site \- https://jobs.citizensbank.com/benefits.
\#LI\-Citizens1
*Some job boards have started using jobseeker\-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.*
Equal Employment Opportunity
Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague’s or a dependent’s reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.
Background Check
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Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.
Benefits
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We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and more.
Awards We've Received
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Dave Thomas Foundation’s Best Adoption\-Friendly Workplace
Disability:IN World's Top Disability Inclusive Business
Glassdoor
Best Place to Work in Consulting, Finance \& Insurance
Human Rights Campaign Corporate Equality Index 100 Award
Newsweek America's Most Charitable Company
The Banker's
US Bank of the Year
Salary Context
This $150K-$190K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Citizens, 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($170K) sits 21% below the category median. Disclosed range: $150K to $190K.
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.
Citizens AI Hiring
Citizens has 2 open AI roles right now. They're hiring across AI/ML Engineer, Data Scientist. Positions span Pittsburgh, PA, US, Columbus, OH, US. Compensation range: $190K - $190K.
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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