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About This Role
Tradeweb is a global leader in electronic trading across asset classes. As financial markets become increasingly interconnected, our technology enables efficient, multi\-asset trading on a global scale. We serve more than 3,000 clients in more than 85 countries, including many of the world’s largest banks, asset managers, hedge funds, insurers, corporations, and wealth managers.
Creative collaboration and sharp client focus have helped fuel our organic growth. We facilitated average daily trading volume (ADV) of more than $2\.8 trillion over the past four fiscal quarters, topping $3\.3 trillion in ADV for the first quarter of 2026\.
Since our IPO in 2019, Tradeweb has completed four acquisitions and doubled our revenues – and 2025 was our 26th consecutive year of record revenues.
Tradeweb plays a central role in modernizing market structure by developing innovative trading protocols, embedding analytics into execution, and building technology infrastructure that supports the convergence of traditional and digitally native financial markets. Tradeweb is a great place to work, recognized in 2025 by Forbes as one of *America’s Best Companies* and by U.S. News \& World Report as one of the *Best Financial Services Companies to Work For* .
Tradeweb Markets LLC ("Tradeweb") is proud to be an EEO Minorities/Females/Protected Veterans/Disabled/Affirmative Action Employer.
Workplace Posters \| U.S. Department of Labor
As a technology\-driven organization, we value individuals who embrace innovation and are eager to leverage emerging technologies, including AI, to improve efficiency, enhance decision\-making, and deliver better outcomes for clients and colleagues. We believe the greatest impact comes from combining technological capabilities with human expertise, judgment, and accountability
Group Details
To capitalize on our success and continued growth plans we are seeking a Cyber Security Architect.
As a member of the information security team, this role will directly contribute to the success of the program and ultimately the company. The role will also have an opportunity to work with subject matter experts not only within security, but across infrastructure, network, development, and business teams.
We look to hire people who are comfortable in working with minimal supervision as part of a team that has consistently delivered ground\-breaking and innovative solutions in one of the most exciting and fast\-moving areas of the of the financial markets. We need people who can prioritize and can effectively articulate complex issues to technical and non\-technical team members.
Tradeweb Technology jobs are fully remote. The Tradeweb Technology hub is in our Jersey City office which can be used for team meetings and collaboration efforts. There may be days where travel to the Jersey City office is recommended for organizational off sites.
Job Responsibilities
- Serve as the enterprise AI Security Architect and trusted advisor for AI initiatives across the organization.
- Define and execute the enterprise AI security strategy, governance framework, and security architecture roadmap.
- Design secure reference architectures for Generative AI, Large Language Models (LLMs), AI agents, Retrieval\-Augmented Generation (RAG), and Machine Learning platforms.
- Establish secure\-by\-design principles and AI security controls across the AI/ML lifecycle.
- Perform end\-to\-end AI security architecture reviews for AI platforms, cloud environments, APIs, and enterprise applications.
- Conduct AI threat modeling using MITRE ATLAS, OWASP Top 10 for LLM Applications, STRIDE, and attack simulation techniques.
- Define and implement security controls to mitigate AI\-specific threats including prompt injection, model poisoning, adversarial attacks, data leakage, model theft, insecure plugins, excessive agency, and supply chain risks.
- Develop security standards for AI infrastructure, model lifecycle management, secure MLOps, model governance, and AI deployment pipelines.
- Partner with engineering, DevSecOps, cloud, and data science teams to embed security throughout AI development and deployment.
- Provide architectural guidance for AI identity and access management, secrets management, data protection, encryption, and privileged access management.
- Lead enterprise AI cyber risk assessments and influence technology investment decisions involving AI adoption.
- Develop AI security blueprints, reference architectures, policies, and governance frameworks aligned with industry standards.
- Drive remediation strategies for AI security vulnerabilities and mentor engineering teams on secure implementation practices.
- Collaborate with legal, privacy, compliance, audit, and risk teams to ensure responsible AI practices and regulatory compliance.
- Build strong partnerships with infrastructure, application development, cloud engineering, and business stakeholders.
- Present AI security strategy, risk posture, and architectural recommendations to executive leadership, regulators, clients, and internal audit teams.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Security, Cybersecurity, Computer Engineering, or a related technical field, or equivalent practical experience.
- 10\+ years of Information Security experience with deep expertise in enterprise security architecture.
- 5\+ years designing enterprise security architectures across cloud\-native and distributed environments.
- Proven experience securing Generative AI, LLMs, AI agents, Machine Learning platforms, and MLOps ecosystems.
- Strong knowledge of AI security principles, adversarial machine learning, AI governance, and model risk management.
- Experience performing AI threat modeling using MITRE ATLAS, OWASP Top 10 for LLM Applications, STRIDE, or equivalent methodologies.
- Expertise in AWS, Azure, or Google Cloud Platform security.
- Strong understanding of secure software development, DevSecOps, Kubernetes, containers, APIs, and cloud\-native application security.
- Experience implementing enterprise Identity and Access Management (IAM), secrets management, encryption, and data protection strategies for AI and cloud environments.
- Experience conducting security architecture reviews, secure code reviews, and application security assessments.
- Working knowledge of NIST AI RMF, NIST CSF, ISO 27001, ISO 42001, CIS Controls, GDPR, and emerging AI regulations.
- Excellent communication and executive stakeholder management skills.
- Financial Services or FinTech experience is preferred.
- Professional certifications such as CISSP, CCSP, AWS Security Specialty, Azure Security Engineer, GIAC, SABSA, or AI Security certifications are desirable.
Additional Information
Tradeweb is committed to providing valuable and competitive benefits. In addition to working in our culture of innovation and collaboration, we offer:
- Health Insurance : Highly competitive medical, dental, and vision programs
- Hybrid Environment : Our employees have the flexibility of working in the office and from home.
- Health Care and Dependent Care Flexible Spending Accounts : You may elect to set aside pre\-tax earnings to pay for eligible health care and dependent day care expenses for you and your eligible family members.
- Maven Family Building Benefit : Maven offers support for fertility and preconception; pregnancy and post\-partum; adoption; surrogacy and pediatrics for children up to age 10\. Tradeweb provide a $10,000 lifetime reimbursement towards fertility, egg freezing, adoption and surrogacy expenses.
- Building Wealth \- 401(k) Savings Plan : Employees are immediately eligible for the 401(k) plan. Participants may contribute up to 75% of eligible compensation into a traditional 401(k) and/or Roth 401(k). Tradeweb will match 100% of the first 4% of compensation that you contribute.
- The current pay range for this role is currently $140,000 to $285,000 per year, based on a regular, full\-time schedule. The amount of pay offered will be determined by a number of factors, including but not limited to qualifications, market data, and internal guidelines.
- This role will also be eligible to participate in Tradeweb’s discretionary bonus program.
- This role is expected to remain open until 8/20/2026\.
Other Benefit Programs
- Pre\-Tax Commuter Benefits Program
- ARAG Legal Services
- Employee Assistance Program
- Tuition Reimbursement
- Financial Wellness Tools
- Travel Assistance Benefits
- Pet Insurance
- Corporate Gym Subsidies
- Wellness Perks
- Paid Time Off and Parental Leave
Salary Context
This $140K-$285K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Tradeweb, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. Disclosed range: $140K to $285K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Tradeweb AI Hiring
Tradeweb has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $285K - $285K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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