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About This Role
JOB REQUISITION
Business Performance Improvement - People & Change AI People Enablement Senior Consultant LOCATION
NEW YORK CITY ADDITIONAL LOCATION(S)
BOSTON, LOS ANGELES, SAN FRANCISCO, WASHINGTON DC - MCLEAN JOB 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 AI People Enablement Senior Consultant to join our growing Business Performance Improvement team.
What You Can Expect
As a Senior Consultant, you will be a mentor, trainer, and coach to Interns and Consultants as you facilitate the successful completion of project work plans. You'll identify areas of risk and opportunities to increase efficiency. You'll strengthen relationships and deepen your abilities to communicate, gain trust, and network with client personnel and professional associates. At the direction of Managers, you may accept responsibility for decision-making in areas including establishing project scope and work plans, project staffing, preparation of deliverables, and application of methodologies.
In this role, you will help clients translate AI investments into sustained workforce adoption, redesigned work, and measurable business value — serving as a bridge between technology deployment and workforce activation.
What Will Help You Be Successful
- You enjoy helping organizations successfully adopt AI by combining workforce activation, organizational design, and workflow transformation.
- You are motivated to learn and interested in all things related to AI adoption and activation, workforce readiness, organization and job design, human-agent workflow redesign, learning and capability building, and value realization, including the latest trends and developments.
- You understand that successful AI transformation isn't achieved through technology deployment alone, but through workforce activation, capability building, and sustained adoption at scale.
- You are passionate about building relationships with clients and providing clients with exceptional experiences.
- You have an inherent interest in project management and team leadership.
- You contribute to a positive team culture that fosters open communication among all engagement team members.
- You create development opportunities for others and ways for your team to improve our clients and communities.
You have interest in working with a diverse portfolio of clients across multiple industries. *
Do Your Talents Include the Following?
- Experience with or understanding of:
- Conducting workforce readiness assessments, stakeholder analyses, and adoption diagnostics to support enterprise AI adoption from pilot through scale.
- Designing and executing activation campaigns, adoption roadmaps, and champion/super-user networks that drive proficiency, utilization, and sustained behavior change.
- Developing role-based learning journeys, AI Academy content, manager enablement toolkits, and learning-in-the-flow-of-work experiences.
- Supporting the design of future-state organizations enabled by AI and human intelligence (AI + HI), including team composition, spans of control, and supervisory models.
- Assisting in defining new roles, responsibilities, decision rights, and accountability models impacted by AI-enabled workflows.
- Facilitating workflow and activity analysis to redesign AI-enabled processes, handoffs, decision points, and human-agent interactions, escalation paths, and governance controls.
- Supporting workforce transformation initiatives, including role-impact assessments, job redesign, and workforce transition plans.
- Assisting with value realization activities, including AI value charters, benefits governance, and tracking expected versus realized value.
- Supporting KPI frameworks and value realization scorecards that connect adoption, productivity, and workforce outcomes to business performance.
- Contributing to workforce/capacity analyses, cost-benefit assessments, and business cases that link workforce change to financial outcomes.
- Developing executive-ready communications, presentations, and client deliverables.
- Evaluating, summarizing, organizing, and interpreting workforce, adoption, and organizational data.
- Establishing and cultivating business relationships and a professional network.
- Ability to translate and communicate AI adoption, workforce, and organizational issues, risks, or opportunities to client personnel, including executives.
Supervisory experience of teams including mentoring, oversight and review of work, coordination across teams, and understanding how to motivate.
*
Your Educational and Professional Qualifications
- Bachelor's degree in a relevant discipline.
- 2+ years working in organizational change, workforce transformation, organization design, change management, learning and development, HR transformation, operating model design, value realization, or a related field, either in professional services or industry.
- Experience supporting technology, digital, automation, or AI-enabled transformation programs strongly preferred.
- Exposure to organization design, workforce planning, operating model design, job architecture, champion networks, or benefits realization/value governance is a plus.
- Familiarity with tools such as OrgVue, Celonis, Microsoft Copilot, Anthropic Claude, Agentforce, or other AI-enabled work platforms is a plus.
- Strong facilitation, stakeholder engagement, and executive communication skills.
- Proficiency in Microsoft Office suite applications with specific emphasis on Word, Excel and PowerPoint.
- Professional Certification such as PROSCI, SHRM-CP, SHRM-SCP, PMP or similar is a plus.
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.
$104,000.00 - $156,000.00 Our annual bonus plan provides eligible employees additional cash and/or discretionary stock compensation opportunities. Below is the bonus target opportunity for this job.
10% 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.
$114,400.00 - $171,600.00 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 [email protected] 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 $104K-$171K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 1356 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 8,943 AI roles we're tracking, AI/ML Engineer positions make up 75% 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 $212,000 based on 11,866 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $228,700. This role's midpoint ($137K) sits 35% below the category median. Disclosed range: $104K to $171K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
Protiviti AI Hiring
Protiviti has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span New York, NY, US, Chicago, IL, US. Compensation range: $171K - $226K.
Location Context
AI roles in New York pay a median of $221,000 across 2,878 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 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). 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 (175) are outnumbered by mid-level (4,132) and senior (3,268) 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 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 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 $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. 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 $253,100 median, while Prompt Engineer roles sit at $141,440. 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 (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 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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