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JOB REQUISITION
Security of AI Associate DirectorLOCATION
NEW YORK CITYADDITIONAL LOCATION(S)
BOSTON, WASHINGTON DC \- MCLEANJOB DESCRIPTION
You Belong Here
The Protiviti Career provides opportunity to learn, inspire, and advance within a collaborative and inclusive culture. We hire curious individuals for whom learning is a passion. We lean into our mission: We Care. We Collaborate. We Deliver.
At every level, we champion leaders who live our values of integrity, inclusion, innovation, and commitment to success. Imagining our work as a journey, we believe integrity guides our way, inclusion moves us forward together, innovation creates new destinations, and our commitment to success empowers us to deliver on our vision to be the most trusted global consulting firm.
Where We Need You
Protiviti is looking for an experienced Associate Director to help build and be a leader in the Security of AI practice within the Cybersecurity \& Resilience team.
The Security of AI discipline is one of the fastest\-moving areas in enterprise risk today. Every organization deploying AI — whether building proprietary models, integrating LLMs, or standing up agentic workflows — needs to answer hard questions about threat modeling, governance, red teaming, model integrity, and data security. We’re helping them answer those questions, and we need a successful leader who can drive that work technically, commercially, and intellectually.
What You Can Expect
As an Associate Director, you will lead client engagements at the intersection of AI adoption and security risk. You will develop lasting relationships with client executives and serve as a trusted advisor across the full arc of their AI security journey — from initial risk assessment and governance design through red teaming, secure architecture, and ongoing monitoring. You will also mentor, train, and coach senior consultants and managers as you build the next generation of AI security practitioners in the practice.
- Lead Security of AI engagements — AI risk assessments, threat modeling for LLM\-integrated applications, agentic system security reviews, red team exercises, and governance program design
- Shape and advance Protiviti's Security of AI service offerings. Partner with practice leadership to evolve methodology, tooling, and delivery accelerators that keep our offerings aligned with emerging client needs and market direction.
- Develop the practice. Help recruit, mentor, and retain top talent. Coach managers and senior consultants on technical depth, client delivery, and career growth within the AI security space.
- Support business development. Lead and contribute to client pursuits, develop proposals, and collaborate with directors and managing directors on account strategy and expansion within priority accounts.
- Build Protiviti's external presence in AI security. Contribute thought leadership through publications, speaking engagements, and participation in industry working groups to strengthen brand recognition and market positioning.
What Will Help You Be Successful
- You have a genuine point of view on how AI is changing the threat landscape — and you’ve been building and testing that view hands\-on, not just reading about it.
- You are comfortable operating at the executive level. You can walk a CISO through an AI risk assessment, explain prompt injection to a board, and translate governance requirements into engineering guidance — all in the same engagement.
- You don’t wait for the industry to catch up. When a new attack vector, model architecture, or regulatory development surfaces, you find out about it on your own and start forming a view before your clients ask.
- You care about the business outcome, not just the security finding. You understand that the goal is to help clients move faster with AI, not to slow them down, and your recommendations reflect that.
- You want to build something. You see this role as an opportunity to shape a practice, define service lines, and leave a mark on how the profession approaches AI security — not just execute on someone else’s playbook.
- You care about developing the people around you. You want to be the reason someone two or three levels below you becomes the next senior leader in this space.
Do Your Talents Include the Following?
- 8\+ years in cybersecurity, with meaningful depth in at least one of: security architecture, AI/ML security, application security, cloud security, or security consulting
- Direct experience with AI security risks — prompt injection, data poisoning, model inversion, supply chain threats in ML pipelines, agentic system access control, or LLM\-integrated application security
- Familiarity with the emerging AI security and governance landscape: OWASP Top 10 for LLMs, NIST AI RMF, MITRE ATLAS, EU AI Act, and sector\-specific AI risk guidance
- Track record of owning client relationships and managing multi\-workstream engagements from kickoff through delivery
- Strong communicator. You can explain AI risk to a security engineer, a CISO, and a board — without changing the substance
- Experience leading and developing teams of consultants and senior consultants
Your Educational and Professional Qualifications
- Bachelor’s degree in a relevant discipline (Computer Science, Computer Engineering, Management Information Systems, Mathematics, or similar) or equivalent demonstrated experience
- 8\+ years working in cybersecurity, with at least 3 years in professional services, consulting, or a client\-facing advisory role
- Proficiency in Microsoft Office suite applications with specific emphasis on Word, Excel, and PowerPoint
- Professional certification such as CISSP, CISM, CCSP, CISA, or equivalent preferred
Our Hybrid Workplace
Protiviti practices a hybrid model, which is a combination of working in person with a purpose and working remotely. This model creates meaningful experiences for our people and our clients while offering a flexible environment. The ratio of remote to in\-person requirements vary by client, project, team, and other business factors. Our people work both in\-person in local Protiviti offices and on client sites, which can include local or out\-of\-state travel based on our projects and client requests and commitments.
*Protiviti is not registered to hire or employ personnel in the following states* *– West* *Virginia, Alaska.*
Starting salary is based on a full\-time equivalent schedule. Placement in the range is dependent upon experience, skills and geographic work location. Below is the salary range for this job.
$165,000\.00 \- $282,000\.00
Our annual bonus plan provides eligible employees additional cash and/or discretionary stock compensation opportunities. Below is the bonus target opportunity for this job.
16%
The total cash range is estimated from the sum of the base salary range plus the bonus target opportunity. Below is the estimated total cash range for this job.
$191,400\.00 \- $327,120\.00
Employees are eligible for medical, dental, and vision coverages, FSA and HSA healthcare accounts, life and accident insurance, adoption and fertility assistance, paid parental leave up to 10 weeks, and short/long term disability. We offer eligible employees a company 401(k) savings and investment plan with an employer match of 50% on the first 6% of your contributions. We provide Choice Time Off (CTO) for vacation, personal needs, and sick time. The amount of (CTO) varies based on years of service. New hires receive up to 20 days of CTO per calendar year. Protiviti also recognizes up to 11 paid holidays each calendar year.
Learn more about the variety of rewards we offer at Protiviti at https://www.protiviti.com/sites/default/files/2026\-01/2026\_u.s.\_benefit\_highlights.pdf.
Any benefits outlined are part of our reward offerings for full\-time employees in the U.S. Your Open Enrollment materials, insurance contracts, plan documents and Summary Plan Descriptions together comprise the official plan document which legally governs the administration of your benefit plans. Protiviti reserves the right to terminate or amend your benefit plans in any way and at any time.
Protiviti is an Equal Opportunity Employer. M/F/Disability/Veteran
As part of Protiviti’s employment process, any offer of employment is contingent upon successful completion of a background check.
Protiviti is committed to being an equal employment employer offering opportunities to all job seekers, including individuals with disabilities. If you believe you need a reasonable accommodation in order to search for a job opening or to apply for a position, please contact us by sending an email to HRSolutions@roberthalf.com or call 1\.855\.744\.6947 for assistance.
In your email please include the following:
- The specific accommodation requested to complete the employment application.
- The location(s) (city, state) to which you would like to apply.
For positions located in San Francisco, CA: Protiviti will consider qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
For positions located in Los Angeles County, CA: Protiviti will consider for employment qualified applicants with arrest or conviction records in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
Protiviti is not registered to hire or employ personnel in the following states – West Virginia, Alaska.
Protiviti is not licensed or registered as a public accounting firm and does not issue opinions on financial statements or offer attestation services.
JOB LOCATION
NY PRO NEW YORK CITY
Salary Context
This $165K-$327K range is above the 75th percentile 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 Protiviti, 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 in Demand for This Role
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. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($246K) sits 12% above the category median. Disclosed range: $165K to $327K.
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.
Protiviti AI Hiring
Protiviti has 6 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Chicago, IL, US, Dallas, TX, US, New York, NY, US. Compensation range: $180K - $327K.
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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