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About This Role
Location: New York, NY, United States
Date Posted: Aug 14, 2026
About Alvarez \& Marsal
Alvarez \& Marsal (A\&M) is a global consulting firm with entrepreneurial, action\- and results\-oriented professionals. We take a hands\-on approach to solving our clients' problems and assisting them in reaching their potential. Our culture celebrates independent thinkers and doers who positively impact on our clients and shape our industry.
The collaborative environment and engaging work—guided by A\&M's core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity—are why our people love working at A\&M.
The Team
A\&M is seeking an Enterprise AI Solutions Architect to sit at the intersection of enterprise architecture, AI engineering, product, and practical technology delivery. This role will be responsible for designing and delivering scalable, secure, AI\-enabled solutions that help the organization move faster, eliminate manual work, and drive measurable business outcomes.
This is a senior technical architecture role that is approximately 50% hands\-on. The successful candidate will not only define solution architecture and technical direction but will also actively participate in building, prototyping, coding, integrating, and troubleshooting solutions.
The Enterprise AI Solutions Architect will work closely with product managers, business stakeholders, internal development teams, and external development partners to translate business requirements into scalable technical architectures and production\-ready solutions.
The role will provide technical leadership to internal and offshore development teams while remaining directly involved in development and implementation. Strong architecture expertise, hands\-on engineering capabilities, organizational skills, and the ability to communicate effectively with both technical and non\-technical stakeholders are essential.
How You Will Contribute
Solution Architecture \& Technical Strategy
Own the end\-to\-end architecture of enterprise AI and technology solutions across frontend applications, backend services, APIs, data platforms, AI services, integrations, and Azure cloud infrastructure.
Translate business and product requirements into scalable, secure, maintainable solution architectures and define the technical roadmap required to move solutions from concept through production.
Develop architecture diagrams, solution designs, integration patterns, data flows, technical specifications, and implementation approaches that provide clear direction to development teams.
Hands\-On Architecture \& Development – Approximately 50%
- Maintain significant hands\-on involvement throughout the development lifecycle, spending approximately 50% of the role actively hands on \- designing, building, prototyping, coding, integrating, leading developers and troubleshooting solutions.
- Develop proofs of concept and production components, particularly for complex AI, integration, API, and cloud architecture challenges.
- Work directly with developers on\- and off\-shore to solve difficult technical problems, review and improve code, validate architectural approaches, and ensure that architecture decisions translate effectively into working software.
AI Solution Architecture
- Architect and develop enterprise AI solutions using Azure, Generative AI, Agentic AI, LLMs, Retrieval\-Augmented Generation (RAG), vector databases, embeddings, orchestration frameworks, APIs, and related technologies.
- Evaluate AI technologies, frameworks, platforms, and architectural approaches and determine the appropriate solution based on business requirements, scalability, security, performance, maintainability, and cost.
- Design AI solutions that can move successfully from proof of concept into secure, reliable, enterprise\-scale production environments.
Key Functions:
- Product \& Business Partnership
- Technical Leadership \& Delivery
- Engineering Standards \& Governance
- Stakeholder Communication
- Problem Discovery \& Innovation
- Team Leadership
Qualifications
- 10\+ years of software engineering, solution architecture, or full\-stack development experience, including at least 6 years as a Solution Architect, Enterprise Architect, Technical Architect, or comparable senior technical role.
- Demonstrated ability to operate as a hands\-on architect, with current technical skills and the ability to spend approximately 50% of the role designing, coding, prototyping, integrating, and troubleshooting solutions.
- Deep experience designing and deploying enterprise solutions within Microsoft Azure.
- Generative AI and/or Agentic AI technologies and architectures.
- Hands\-on experience building AI\-powered applications using technologies such as LLMs, RAG architectures, vector databases, embeddings, AI agents, orchestration frameworks, and modern AI SDKs.
- Demonstrated experience designing distributed systems, scalable integrations, APIs, event\-driven architectures, and multi\-team delivery models.
- Strong understanding of enterprise architecture principles including scalability, security, reliability, resiliency, observability, maintainability, and performance.
- Experience taking AI solutions from proof of concept through enterprise production deployment.
- Proven experience providing technical leadership to internal, offshore, and/or external development teams.
- Strong understanding of software engineering practices including source control, code review, automated testing, CI/CD, DevOps, monitoring, and production support.
- Demonstrated ability to work directly with product managers and business stakeholders from discovery and requirements gathering through architecture, implementation, and production delivery.
- Exceptional communication and interpersonal skills, with the ability to communicate complex architecture and technology concepts clearly to technical teams, business leaders, and executives.
- Demonstrated ability to operate effectively in ambiguous environments and establish structure and technical direction where requirements are not fully defined.
- Knowledge of enterprise identity and security standards including SSO, SAML, OAuth/OIDC, role\-based access controls, audit logging, data protection, and compliance controls.
- Experience managing or providing technical direction to offshore development teams is strongly preferred.
Your journey at A\&M
We recognize that our people are the driving force behind our success, which is why we prioritize an employee experience that fosters each person’s unique professional and personal development. Our robust performance development process promotes continuous learning, rewards your contributions, and fosters a culture of meritocracy. With top\-notch training and on\-the\-job learning opportunities, you can acquire new skills and advance your career.
We prioritize your well\-being, providing benefits and resources to support you on your personal journey. Our people consistently highlight the growth opportunities, our unique, entrepreneurial culture, and the fun we have together as their favorite aspects of working at A\&M. The possibilities are endless for high\-performing and passionate professionals.
Regular employees working 30 or more hours per week are also entitled to participate in Alvarez \& Marsal Holdings’ fringe benefits consisting of healthcare plans, flexible spending and savings accounts, life, AD\&D, and disability coverages at rates determined periodically as well as a 401(k) retirement savings plan. Provided the eligibility requirements are met, employees will also receive an annual discretionary contribution to their 401(k) retirement savings plan from Alvarez \& Marsal. Additionally, employees are eligible for paid time off including vacation, personal days, seventy\-two (72\) hours of sick time (prorated for part time employees), ten federal holidays, one floating holiday, and parental leave. The amount of vacation and personal days available varies based on tenure and role type. Click here for more information regarding A\&M’s benefits programs.
The salary range is $195,000\- $230,000 annually, dependent on several variables including but not limited to education, experience, skills, and geography. In addition, A\&M offers a discretionary bonus program which is based on a number of factors, including individual and firm performance. Please ask your recruiter for details.
Culture \& Values
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At Alvarez \& Marsal, our core values of Integrity, Quality, Objectivity, Fun, Personal Reward, and Inclusive Diversity guide everything we do, shaping a culture rooted in entrepreneurship, impact, and integrity. We trust our people to take ownership early, contribute to meaningful challenges, and drive results that matter. We empower growth and champion diverse perspectives. Above all, we value doing the right thing. For those ready to roll up their sleeves, lead with integrity, and be difference makers, this is where it starts.
Equal Opportunity Employer
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It is Alvarez \& Marsal’s practice to provide and promote equal opportunity in employment, compensation, and other terms and conditions of employment without discrimination because of race, color, creed, religion, national origin, ancestry, citizenship status, sex or gender, gender identity or gender expression (including transgender status), sexual orientation, marital status, military service and veteran status, physical or mental disability, family medical history, genetic information or other protected medical condition, political affiliation, or any other characteristic protected by and in accordance with applicable laws. Employees and Applicants can find A\&M policy statements and additional information by region here.
Unsolicited Resumes from Third\-Party Recruiters
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Please note that as per A\&M policy, we do not accept unsolicited resumes from third\-party recruiters unless such recruiters are engaged to provide candidates for a specified opening. Any employment agency, person or entity that submits an unsolicited resume does so with the understanding that A\&M will have the right to hire that applicant at its discretion without any fee owed to the submitting employment agency, person or entity.
Salary Context
This $195K-$230K range is above the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 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 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Alvarez & Marsal, 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 $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. Disclosed range: $195K to $230K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Alvarez & Marsal AI Hiring
Alvarez & Marsal has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span New York, NY, US, Atlanta, GA, US. Compensation range: $95K - $230K.
Location Context
AI roles in New York pay a median of $220,000 across 1,650 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 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 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 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). 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 (138) are outnumbered by mid-level (2,071) and senior (1,655) 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 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 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 $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. 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 $287,500 median, while Prompt Engineer roles sit at $145,000. 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 (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 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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