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About This Role
JOB REQUISITION
Digital Identity Non\-Human Identity, Machine Identity \& Agentic Identity Associate DirectorLOCATION
CHICAGOADDITIONAL LOCATION(S)
ATLANTA \- PEACHTREE RD, AUSTIN, CHARLOTTE, DALLAS, HOUSTON, MIAMI, ORLANDO, PHILADELPHIA, TAMPAJOB 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 a Technology Consulting Associate Director to join our growing Digital Identity team with a specialization in Non\-Human Identity (NHI), Machine Identity, Workload Identity, and Emerging Agentic Identity.
This leader will help clients address one of the fastest\-growing challenges in cybersecurity: securing and governing identities used by applications, services, cloud workloads, APIs, automation platforms, DevOps pipelines, machines, bots, and AI agents.
The ideal candidate combines executive\-level client advisory skills, strong business development and market\-facing capabilities, architect\-level technical expertise, experience leading complex cybersecurity and identity programs, and passion for shaping emerging identity capabilities within the AI era.
This individual will play a key role in expanding Protiviti's market presence, developing new service offerings, mentoring practitioners, supporting strategic pursuits, and leading transformative identity initiatives across Fortune 500 organizations.
What You Can Expect
- As an Associate Director, you'll take a lead role in strengthening our relationships with clients and providing seamless guidance in the completion of engagements. You'll partner with our strategic clients to manage risk associated with their use of technology.
- You'll develop strategies to solve complex business problems using new ways of thinking, and devise solutions to support your clients' needs through analytics, automation or the latest tools and methods.
- Partner with clients and alliance partners to identify opportunities and develop technology\-enabled solutions focused on identity security.
- Serve as a trusted advisor to CISOs, IAM leaders, cloud security leaders, enterprise architects, and platform engineering teams.
- Lead client engagements spanning strategy, assessments, architecture design, implementation oversight, operating model design, governance, and roadmap development.
- Develop lasting client relationships and expand Protiviti's presence in the market.
- Help define Protiviti's point of view related to Non\-Human Identity, Machine Identity, Agentic Identity, and Identity Security for AI.
- Support proposal development, business development activities, alliance relationships, and thought leadership initiatives.
- Mentor and develop consulting teams while overseeing the successful execution of project work plans.
- Collaborate across Protiviti practices including Cybersecurity, Cloud Security, AI Security, Data Security, Infrastructure, and Application Security.
What Will Help You Be Successful
- Helping organizations secure identities beyond traditional workforce users.
- Advising executive stakeholders on emerging risks associated with machine identities, cloud\-native identities, automation, and AI agents.
- Translating complex identity architecture concepts into practical business outcomes and measurable risk reduction.
- Solving challenges that span IAM, PAM, IGA, cloud security, application security, and DevSecOps domains.
- Building trusted relationships with clients and alliance partners.
- Developing market\-leading service offerings and go\-to\-market strategies.
- Leading technical and business discussions across diverse stakeholder groups.
- Building and mentoring high\-performing consulting teams.
- Contributing to proposals, sales pursuits, and thought leadership initiatives.
- Staying at the forefront of evolving identity trends, platforms, and security challenges.
Do Your Talents Include the Following?
Identity Strategy and Advisory
- Experience delivering strategic IAM, PAM, NHI, or Machine Identity advisory services, including assessments, maturity evaluations, strategy development, and roadmap creation.
- Experience designing enterprise operating models and governance frameworks for identity programs.
- Ability to communicate technical and business risks to executive stakeholders and boards.
- Experience developing identity security standards, policies, and control frameworks.
Non\-Human Identity and Machine Identity
- Hands\-on experience securing and governing non\-human identities including service accounts, application accounts, service principals, API keys, workload identities, container identities, automation accounts, bot identities, and AI\-powered agents.
- Experience addressing credential sprawl, secrets management, token lifecycle management, certificate lifecycle management, privileged service account governance, identity ownership and accountability, least privilege implementation, and identity discovery and inventory.
- Experience designing lifecycle processes for creation, ownership, approval, monitoring, certification, review, and retirement of machine identities.
- Hands\-on experience in architecting and implementing NHI/Secrets management solutions aligning with leading NHI frameworks such as OWASP.
Architecture and Technical Leadership
- Architect\-level understanding of IAM capabilities including IGA, PAM, Access Management, authentication and authorization, and Identity Threat Detection \& Response (ITDR).
- Experience designing secure identity architectures leveraging OAuth, OpenID Connect, SAML, SCIM, JWTs, service\-to\-service authentication, and federated workload identity.
- Experience designing or evaluating secrets management solutions, certificate lifecycle management solutions, key management architectures, cloud\-native identity platforms, API authorization patterns, and Zero Trust architectures.
Cloud and Platform Security
- Experience with one or more of the following: Microsoft Entra ID, Azure Managed Identities, AWS IAM, Google Cloud IAM, Kubernetes, container platforms, CI/CD platforms, Infrastructure\-as\-Code environments, and cloud\-native workload identity solutions.
Emerging Agentic Identity and AI Security
- While direct experience with Agentic Identity is not required, successful candidates will demonstrate experience applicable to AI\-enabled identity use cases, including identity governance for autonomous systems, delegated authorization models, service\-to\-service authentication, automation and orchestration platforms, AI\-enabled applications and workflows, human accountability models for non\-human actors, secure access patterns for AI systems, and governance and lifecycle management of AI agents and autonomous workloads.
Business Development and Market Leadership
- Identifying client challenges and converting them into consulting opportunities.
- Developing executive presentations, proposals, points of view, and solution offerings.
- Building relationships with alliance partners and technology vendors.
- Contributing to sales pursuits and revenue growth.
- Speaking at industry events, webinars, client workshops, and executive briefings.
- Supporting practice development and market expansion initiatives.
Leadership Experience
- Leading cross\-functional consulting teams.
- Coaching and mentoring professionals.
- Conducting performance feedback and career development discussions.
- Managing multiple complex engagements simultaneously.
- Operating effectively in a fast\-paced, matrixed consulting environment.
Experience With the Following Technologies is Preferred
- CyberArk (Conjur), SailPoint, Saviynt, Veza, Delinea, Okta, Ping Identity, Microsoft Entra, Venafi, HashiCorp Vault, AWS IAM, Kubernetes, BeyondTrust, Akeyless, Oasis Security, Token, Clutch, and other NHI, PAM, and Identity Security platforms.
Your Educational and Professional Qualifications
- Bachelor’s degree in a relevant discipline (e.g., Information Systems, Computer Science, Engineering, Cybersecurity)
- 9\+ years working in IAM, PAM, cybersecurity consulting, cloud security, or related fields.
- Experience within a consulting firm, systems integrator, software vendor, or large enterprise identity program is strongly preferred.
- Professional certifications are strongly preferred, including CISSP, CCSP, Microsoft security certifications, CyberArk certifications, SailPoint certifications, Saviynt certifications, AWS certifications, and vendor\-specific IAM or PAM credentials. Experience building or leading a Machine Identity or Non\-Human Identity program.
- Experience with service account governance initiatives.
- Experience with certificate lifecycle management programs.
- Experience implementing workload identity federation.
- Experience securing AI\-enabled applications or autonomous systems.
- Experience developing NHI security offerings, thought leadership, or market strategies.
- Existing relationships with IAM, PAM, Cloud Security, DevOps, or AI Security leaders.
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.
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.
$155,000\.00 \- $264,000\.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.
$179,800\.00 \- $306,240\.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
IL PRO CHICAGO
Salary Context
This $155K-$306K 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 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. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($230K) sits 5% above the category median. Disclosed range: $155K to $306K.
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 Chicago pay a median of $205,100 across 97 tracked positions. That's 6% below 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 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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