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About This Role
JOB REQUISITION
AI ML Solution Architect \& Developer ManagerLOCATION
NEW YORK CITYADDITIONAL LOCATION(S)
LOS ANGELES, 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 a Technology Consulting Manager to join our growing Artificial Intelligence \& Machine Learning (AI/ML) team.
What You Can Expect
Protiviti is an innovative global consultancy that provides transformative solutions across industries through its deep expertise in artificial intelligence. Protiviti works with clients to design AI that is innovative to drive optimal results, put transparent controls in place, and champion user adoption, ensuring that AI brings measurable value while maintaining the highest standards of safety and accountability.
As a Manager, you’ll partner with our clients to solve complex business problems and provide impactful advice and solutions. You will develop lasting relationships with client personnel and further these relationships through quality product delivery. You will foster a network within the business community and serve as an ambassador of Protiviti in the market. You will also be a mentor, trainer, and coach to Consultants and Senior Consultants as you facilitate the successful completion of project work plans.
What Will Help You Be Successful
- You enjoy discussing technical and industry trends and seek opportunities to demonstrate AI technologies and enable both internal and external stakeholders.
- You are motivated to learn and interested in all things related to AI ML, including the latest trends and developments.
- You excel at using storytelling techniques to bring AI concepts and ideas to life, making complex technologies accessible, and engaging diverse audiences.
- You have an inherent interest in project management and team leadership.
- You promote a positive team culture that fosters open communication among all engagement team members.
- You create development opportunities for others, including participating in the creation and rollout of training, and ways for your team to improve our clients and communities.
- You participate in the initiation and development of new products and services.
- You understand the business environment and potential impact of Artificial Intelligence within industries.
- You have interest in working with a diverse portfolio of clients across multiple industries.
Do Your Talents Include the Following?
- Demonstrated experience with:
- Hands\-on development of end\-to\-end AI solutions to solve complex business problems.
- Cloud services and infrastructure with platforms such as AWS, Microsoft Azure, or Google Cloud.
- Have built or deployed systems powered by LLMs or generative models and understand how model behavior affects product experience.
- Proficiency in programming languages for AI development such as Python, R, or SQL, with experience in libraries/frameworks such as TensorFlow, PyTorch, Scikit\-learn, Langchain, etc.
- Experience with big data technologies such as Hadoop and Spark.
- Implementing required security and privacy controls when developing AI\-enabled prototypes, including proper data handling, masking/anonymization, and secure storage based on defined standards.
- Applying cloud platform security features (e.g., encryption, identity and access management, secure API integrations) to ensure AI applications adhere to enterprise and regulatory requirements.
- Executing security\-related tasks such as integrating authentication, enforcing role\-based access, and configuring secure data pipelines as part of delivering production\-ready AI solutions.
- Identifying and addressing security or privacy considerations during development and proactively collaborating with security stakeholders to validate implementation.
- Documenting security\-relevant design decisions, data flows, and privacy considerations to support Responsible AI practices and audit transparency.
- Collaborating with internal stakeholders to create AI\-enabled solutions for repeatable business problems and develop functional prototypes to validate feasibility and applicability of AI technologies to practical use cases and challenges.
- Fostering innovation by identifying new AI technologies or methodologies that can enhance current processes or solve new challenges.
- Establishing best practices in AI governance principles ensuring ethical use, transparency, risk management while delivering high\-quality services to clients.
- Leadership and direct supervisory experience of teams include conducting performance appraisals, mentoring and coaching, 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 (e.g., Computer Science or related field).
- 5\+ years working in professional services or industry.
- A minimum of 3\-year hands\-on experience with Generative Artificial Intelligence technology experimentation, prototyping, solutioning and deployment.
- Familiarity with cloud\-based AI technologies and platforms is strongly preferred.
- Professional Certification such as AWS Certified Solutions Architect or Azure Solutions Architect are 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 varies 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.
$145,000\.00 \- $232,000\.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.
12%
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.
$162,400\.00 \- $259,840\.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 $145K-$259K 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 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. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($202K) sits 7% below the category median. Disclosed range: $145K to $259K.
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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