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About This Role
Job ID: 17812 Business Unit: MTA Headquarters Location: New York, NY, United States Regular/Temporary: Regular Department: IT CISO Date Posted: Oct 23, 2026 Description
JOB TITLE:
Cybersecurity Office Manaher, AI Security Enablement
SALARY RANGE:
$148,784 - $196,730
DEPT/DIV:Information Technology
SUPERVISOR:Deputy Chief Cybersecurity Officer
LOCATION:
2 Broadway, New York, NY 10004
HOURS OF WORK:9:00 am - 5:30 pm (7.5 hours/day) or as required
This position is eligible for teleworking, which is currently 2 days per week. New hires are eligible to apply 30 days after their effective date of hire.
Opening:
The Metropolitan Transportation Authority is North America's largest transportation network, serving a population of 15.3 million people across a 5,000-square-mile travel area surrounding New York City, Long Island, southeastern New York State, and Connecticut. The MTA network comprises the nation’s largest bus fleet and more subway and commuter rail cars than all other U.S. transit systems combined. MTA strives to provide a safe and reliable commute, excellent customer service, and rewarding opportunities.
Summary:
The purpose of this position is to provide technical leadership and management of MTA's cyber security program in one or more technical domains.
This role deals with both internal and external threats to the MTA systems which can affect both the safety of employees and customers, system integrity, and availability of operations.
As part of managing the program, the Cybersecurity Officer will need expertise in managing a complex program with highly skilled staff, contracts, and processes associated with risk management that are essential to maintaining electronic and physical safety for MTA's business in all areas that utilize technology (Corporate, Customer Facing and Informational, Fare Payment/PCI, Operational Technologies, 3rd Party Managed, Vendors, etc.).
The Cybersecurity Officer will be responsible for managing and developing staff, technology, and processes to reduce risk with the evolved cyber threat landscape and changing technology portfolio.
This position works across multiple technology and cybersecurity domains to ensure cybersecurity is looked at holistically from user, data and component, and systems perspectives.
The position also considers all risk assessments, data driven analytics, and actively seeks to develop and maintain standards, reference architectures, and reduce risk of the MTA through emerging technologies and trends in the industry.
The position is expected to have a level of expertise in one or more domains of technology effective management. There is a long list of these specialized domains in the cybersecurity field and this list is growing and everchanging as the field evolves and as risks and circumstances change.
The assigned cybersecurity domain may include AI Security Enablement, supporting the safe and effective adoption of Artificial Intelligence, Generative AI, AI-enabled capabilities, automation, and agentic technologies across business and cybersecurity functions. The position may coordinate AI use cases, practical risk-based guidance, workforce enablement, technical experimentation, and adoption of AI capabilities that improve organizational and cybersecurity effectiveness.
Responsibilities:
- Leadership + Provide leadership to a strong talent pool of technical professionals. + Lead a team of multi-functional technical staff planning, building, and maintaining cybersecurity tools, configurations, and risk mitigation to support Information and Operational Technology applications and/or infrastructure products. + Lead others, as appropriate, and when necessary, that will consist of one or more agile coaches, data analytic researchers and other cybersecurity personnel . + Provide leadership in development of inter-team communication and cohesiveness; sustain culture and supporting assigned staff during organizational growth/changes. + Provide direction on evaluation, selection, implementation, and maintenance of cybersecurity tools, processes, and techniques for their assigned cyber domains and products, ensuring appropriate investment in strategic and operational systems. + Leads teams to complete projects when a project manager has not been assigned. + Attain significant achievements managing technical teams, contractors and vendors.
- Human Resource Management + Attract, develop, coach and retain high-performance team members, empowering them to elevate their level of responsibility, span of control and performance in conjunction with the Cybersecurity Management and IT Workforce Planning & Workload Management office. + Build staff expertise and competence to meet evolving demands within the Enterprise Product Management unit.
- Financial Management + Demonstrate consistent understanding of funding, communications and systems; recommend timelines and resources needed to achieve the program goals. + Collaborates with IT Business Management Services to identify procurement contracts to support program related activities.
- Strategy & Planning + Assesses and makes recommendations on the improvement and re-engineering within the IT Department and work with the stakeholders at keeping the total cost of ownership down. + Promotes the use of employee self -service and mobile connectivity within products to reduce the reliance on paper. + Recommends and supports automation of business processes by creating in-line forms and approvals, reducing the reliance on manual approvals that could be untimely. + Uses judgment to form conclusions that may challenge conventional wisdom
- Acquisition & Deployment + Coordinates and facilitates consultation with stakeholders to define business and systems requirements for new technology implementations, developing business case and cost justifications for such initiatives. + Provides direction on evaluation, selection, implementation and maintenance of information systems, ensuring appropriate investment in strategic and operational systems. + Advises MTA IT management, as information becomes available, on changing trends and emerging technology and their potential use within the MTA. + Directs the development of the analysis required to determine if Information Technology projects should follow a “Build” (develop with in-house staff) or “Buy” (cloud or packaged solution) methodology. + Manages the development and implementation of new modules within assigned products. + Advises on the selection, prioritization, development, and implementation of products as they relate to the selection, acquisition, development, and installation of MTA IT and OT Security, applications, and infrastructure.
- Management and Oversight + Participates in overall business planning, bringing current knowledge and future vision of technology and systems as related to the company’s goals. + Responsible for leading and reporting on various product progress and deliverables ensuring that the IT/OT needs of the MTA are met on time and within budget, including identifying weekly, monthly and annual performance targets to show progress on IT product work and OT objectives. + Ensure continuous delivery of product services through oversight of service level agreements with end users and monitoring of product performance. + Responsible for the recruitment, development, motivation, training and retention of a diverse and high performing multi-level IT/OT team professionals, conforming to budgetary objectives and Human Resources policy and programs in conjunction with the IT Workforce Planning & Workload Management office. + Develop business case justifications and cost/benefit analyses for IT spending and initiatives keeping customizations to a minimum and total cost of ownership down.
- Planning + Manage and plan the future technical architecture, providing insight into the future of their area of technology in order to continually improve effectiveness and efficiency. + Manage and plan the development of roadmaps related to their area(s) of expertise to manage and meet identified technology needs. + Manage and plan the evaluation of new technologies relative to their domain(s) to determine applicability to and best meet the needs of MTA and constituent agencies. + Manage and ensure disaster recovery and contingency plans for their domain(s) to provide users with minimal interruptions in service.
- Architecture + Oversees architectural direction for domains under management to meet senior management and cybersecurity goals. + Understands, review, and approve Cybersecurity Reference Architectures and Solutions for applying them + Revalidates systems to the most recent reference architectures to determine gaps, develop and manage programs to align systems to newest standards and reference architectures
- Contracts/Vendor Management + Contribute and own technical elements of RFPs and RFIs and negotiates with vendors on technical issues to ensure results are delivered in line with user and organization requirements. + Manages contracts and expenses to ensure SLAs and contract renewals are processed timely + Provide contract management support to ensure vendor deliverables are met + Manage and lead major projects and assigned service providers with technical expertise to address mission critical issues, evaluates ongoing vendor service level and enforces SLAs and penalties.
- Documentation + Ensure detailed and updated documentation is in place for cybersecurity systems and user processes. + Participate in the creation of enterprise security documents (policies, standards, baselines, guidelines, and procedures) under the direction of the IT Security Manager, where appropriate.
- Guidance, Communications and Training Support + Provides timely and relevant updates to appropriate stakeholders and decision makers + Communicates investigation findings to relevant business units to help improve the information security posture + Provides technical guidance to project managers and senior leadership on cybersecurity and technology strategies + Ensures quality and review and guidance on tests of new systems and manages cybersecurity risks and remediation system testing, baseline, and best practices + Provide escalation support to project teams in their area of expertise to promote technical understanding and talent development + Provide guidance and take input from Analysts, Engineers, Architects, and Technology Subject Matter Experts on cybersecurity and technology best practices, current threat landscape, and a risk management approach for optimal alignment + Provides sound cybersecurity recommendations
- Operations + Provide leadership and advisement when necessary during incident response and provide continuous improvement updates to the threat model for risks to the business and systems + Ensure specific monitoring points are continually updated to assess performance of technologies in their domain(s). Identify and manage the necessary actions to ensure optimal performance and reliability.
- Research & Analysis + Validates and maintains incident response plans and processes to address potential threats + Compiles and analyzes data for management reporting and metrics + Researches emerging technologies and process improvements to stay current and plan for the evolving threat landscape to ensure strategy meetings current threats + Monitors relevant information sources to stay up to date on current attacks and trends + Ensure cybersecurity technology solutions meet strategy meets security framework objectives and business objectives + Hypothesizes new threats and indicators of compromise + Oversee rigorous quality assurance processes to deliver reliability, performance, and safety objectives + Oversees rigorous quality assurance processes to deliver reliability, performance, safety objectives. + Oversees staff workload and quality of work, addressing performance issues when needed.
Required Qualifications:
- Bachelor’s Degree in Arts/Sciences (BA/BS) required, in Computer Science or related fields. An equivalent combination of education and experience may be considered in lieu of a degree.
- Minimum 5 years of relevant experience and leadership ability.
- CISSP, CISM, or other advanced security-related certifications preferred
- Certifications in technology subdomains preferred (ie., Cloud, Applications, Infrastructure, Security Technology, etc.).
- Certifications in Artificial Intelligence, Generative AI, AI security, responsible AI, cloud AI platforms, application security, security architecture, or related emerging technology disciplines preferred.
Knowledge, Skills and Abilities:
- Must possess a deep understanding of technology and cybersecurity domain principles.
- Proven ability to manage projects and initiatives.
- Proven ability to manage people.
- Proven ability to add value to a team.
- Understanding of Operating Systems, Cloud, Mobile, and Applications.
- Understanding of TCP/IP (OSI Layers 1– 4) and Internet and Intranet technologies required (OSI Layers 5-7) required.
- Some Scripting or programming skills (PERL, Python, PowerShell, etc.) preferred as needed.
- Proficient in Productivity Tools (ie. Office 365, Gsuite).
- Prior experience with installing, maintaining, and troubleshooting technology systems.
- Experience with Spreadsheets and Data Analysis.
- Successful track record in design of software systems to meet the current and future needs of a complex organization OR successful track record in design and implementation of IT Infrastructure and related hardware and software technologies to meet the current and future needs of a complex transportation organization.
- Strong Verbal/written communications skills.
- Financial/budgeting planning and management experience is a plus.
- Ability to fit in with the constantly shifting needs and demands of the business Department
- Experience in Project Management Principles (Waterfall and Agile) preferred.
Preferred Technical Skills:
- Preferred experience enabling adoption of AI, Generative AI, automation, cloud, SaaS, or other emerging technologies within a complex enterprise environment.
- Preferred experience identifying, evaluating, prioritizing, prototyping, or operationalizing technology use cases based on business value, cybersecurity risk, technical feasibility, and operational impact.
- Preferred experience applying emerging technology to improve cybersecurity, IT, engineering, risk, or operational processes and measuring resulting efficiency, effectiveness, or risk reduction.
- Preferred experience partnering with business, product, engineering, architecture, data, cloud, infrastructure, cybersecurity, or other technology teams to move new capabilities from experimentation through operational adoption.
- Preferred experience developing technical guidance, reusable patterns, playbooks, training, labs, knowledge resources, communities of practice, or SME/champion programs that improve workforce adoption of emerging technologies.
- Preferred hands-on experience with one or more AI technologies or implementation approaches such as LLMs, model APIs, retrieval-augmented generation (RAG), AI agents, agentic workflows, prompt/context engineering, Model Context Protocol (MCP), AI-enabled automation, or cloud AI platforms.
- Familiarity with scripting, APIs, low-code/no-code automation, cloud platforms, or technical prototyping is strongly preferred; the role is intended to function as a technical player-coach rather than solely as a program, policy, or governance manager.
Core Competencies:
Core Competency
Proficiency Level
Competency Definition
Collaborates
Expert
Building partnerships and working collaboratively with others to meet shared objectives
Cultivates Innovation
Expert
Creating new and better ways for the organization to be successful
Customer Focus
Expert
Building strong customer relationships and delivering customer-centric solutions
Communicates Effectively
Expert
Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiences
Values Diversity
Expert
Recognizing the value that different perspectives and cultures bring to an organization
Cybersecurity Domains:
- Active Directory and Directory Services
- Identity and Access Management
- Privileged Access Management
- Cloud Security (PaaS, SaaS Applications)
- Cloud Security (DevSecOps and Tools)
- Azure and Amazon Web Services Security
- Office 365, Microsoft Dynamics Security
- Application Security (Development and Configuration)
- Application Source Code Security
- Middleware Security
- Database Security
- Network Security Design
- Public Key Infrastructure
- Multifactor Authentication
- Smart Card Technology
- Operating Systems and Systems Hardening
- Desktop, Servers, and Hypervisor Security
- Mobility Security (iOS, Android, Apple, Laptops, etc.)
- Wireless Network Security (WiFi, 5G, RF/Radio, UWB, etc.)
- Carrier Network Security (DWDM, Fiber Optic Network, MPLS, etc.)
- Computer-Based Train Control (CBTC) Security
- Federal / State Regulations and Services
- Onboard Train/Bus Systems Security
- Operational Technology
- Internet of Things
- Capital Program
- Information and Operational Technology Security Training
- Positive Train Control (PTC) Security
- Red Team (OT)
- Building Management Systems
- Video Analytics
- Policy Dispatch Systems
- Mobile Device and Application Security
- Cyber Audits and Compliance
- Data Scientist
- Data Security
- PCI Security and Controls
- Penetration and Vulnerability Tester
- Procurement and Supply Chain
- Red Team (IT)
- Risk Management
- Vulnerability Assessor
- Cybersecurity Training
- Forensic / Investigator
- Incident Response Analyst
- Threat Intelligence and Hunting
- Security Operations Center
- Endpoint Security and Detection Services
Other Information:
Pursuant to the New York State Public Officers Law & the MTA Code of Ethics, all employees who hold a policymaking position must file an Annual Statement of Financial Disclosure (FDS) with the NYS Commission on Ethics and Lobbying in Government (the “Commission”).
Equal Employment Opportunity:
MTA and its subsidiary and affiliated agencies are Equal Opportunity Employers, including with respect to veteran status and individuals with disabilities.
The MTA encourages qualified applicants from diverse backgrounds, experiences, and abilities, including military service members, to apply.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Salary Context
This $148K-$196K range is below the median for AI/ML Engineer roles in our dataset (median: $178K across 2239 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 11,520 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Metropolitan Transportation Authority, 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 $212,040 based on 13,780 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($172K) sits 19% below the category median. Disclosed range: $148K to $196K.
Across all AI roles, the market median is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($266,050) and AI Engineering Manager ($253,461). By seniority level: Entry: $112,320; Mid: $193,200; Senior: $230,000; Director: $272,250; VP: $235,830.
Metropolitan Transportation Authority AI Hiring
Metropolitan Transportation Authority has 2 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $196K - $196K.
Location Context
AI roles in New York pay a median of $221,000 across 3,257 tracked positions. That's 4% above the national 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 11,520 open positions tracked in our dataset. By seniority: 140 entry-level, 5,630 mid-level, 4,176 senior, and 1,574 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (708 positions). The remaining 10,737 roles require on-site or hybrid attendance.
The market median for AI roles is $213,480. Top-quartile compensation starts at $264,000. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($266,050 median, 70 roles); AI Engineering Manager ($253,461 median, 58 roles); Research Engineer ($252,000 median, 476 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 11,520 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (8,769), AI Software Engineer (586), AI Product Manager (511). 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 (140) are outnumbered by mid-level (5,630) and senior (4,176) 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 1,574 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (708 positions), with 10,737 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 $213,480. Top-quartile roles start at $264,000, and the 90th percentile reaches $318,400. 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 $266,050 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 (2,267 postings), Aws (1,178 postings), Azure (972 postings), Rag (924 postings), Gcp (715 postings), Pytorch (586 postings), Claude (572 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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