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About This Role
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West Monroe is looking for an *Advisory Architect, Data/AI due diligence* to join our Technology \& Experience Practice; Transaction Services–Data Engineering \& Analytics and deliver on technology M\&A due diligence projects. The Advisory Architect will partner with other Transaction Services advisors/architects (Cloud, Cyber, Software Engineering, infrastructure) and executive client stakeholders to provide assessment solutions and tech advisory across a variety of industries, including Private Equity, High\-Tech \& Software, Healthcare, and Financial Services. As a technology agnostic firm, they will also have the chance to continuously expand their skillset while working with cutting edge tools, platforms, and frameworks. This is an exciting opportunity to work within our newly formalized (but long existing) technology M\&A offering and lead strategic enterprise projects, advanced analytics due diligences, post\-merger integrations, and carve\-out advisory engagements.
Responsibilities:
- Collaborate with cross functional teams, Transaction Services’ consultants from other competencies (i.e., Software Engineering, Cloud \& Infrastructure, Cybersecurity, Data \& Analytics) in support of holistic, tech due diligence assessments for client M\&A activity and identify growth and remediation opportunities through analysis of existing data and analytics systems, business processes and data monetization opportunities.
- Assess underlying technology/libraries/tooling landscape within enterprise organizations to make recommendations to strategic investors on improving market readiness, achieving long\-term scalability, and/or reducing operational cost
- Formulate strategic investment summaries, key risk mitigation analyses, and long\-term technology\-based strategy for both pre\-close and post\-close projects
- Establish the linkage between business strategy and data strategy (and vice versa) to deliver impactful outcomes
- Executive presence with the ability to present, interpret, and recommend results of work including the development of new concepts, major advances in the field, new major applications, and progress on all product programs.
- Be a thought leader, create white papers and represent the organization at various industry conferences and events
- Provide leadership and mentoring to data engineers/architects/BI analysts and practitioners
- Be the visible face of the data engineering team to internal partners, external customers and prospects, and the data architect community at large
- Be a Subject Matter Expert (SME) for the data platform engineering (ingestion through insights), data strategy, data modeling initiatives across the department’s big data projects.
- Keep pulse of the latest development trends in cloud (AWS, GCP, Azure, etc), data platforms (Databricks, Snowflake etc), databases (RDBMS, SQL, NoSQL, Oracle, etc.), reporting (PowerBI, Quicksight, etc.), ETL/ELT, data warehousing, data hubs, data lakes, data marts etc. and various tools, products, and use cases.
- Expertise in data warehousing approaches (Kimball, Inmon), normalized and de\-normalized data models including dimensional schemas (star, snowflake)
- Strong understanding of streaming (e.g. Kafka, Kinesis), batch\& workflow (e.g. Airflow, AWS Glue, CTTRL\-M) data transport technologies
- Experience with Data Visualization tools including PowerBI, Tableau, Looker, etc
- Drive new business with existing clients by identifying unique opportunities and liaising to appropriate client leads, account managers, or business developers
Qualifications:
- Master’s/Bachelor's Degree in Computer Science, Information Systems, or equivalent relevant work experience
- Minimum 6\-8\+ years of hands\-on professional development experience in data modeling and data design and must have hands on experience implementing solutions
- Consulting firm/industry or start\-up experience preferred
- Experience with the technical programming to access and extract data from diverse sources residing on multiple platforms and implement large, sophisticated data models by combining, synthesizing, and structuring data
- Experience performing complex data migration to and from disparate data systems/platforms as well as to/from the cloud (AWS, Azure, GCP, etc.)
- Good knowledge of standard concepts, best practices, and procedures within a data warehousing and Business Intelligence (BI) environment
- Provide Points of View (POV) and recommendations for cloud\-native, industry\-leading products along with emerging, start\-up offerings
- including proposal development, estimation, and day\-to\-day project management (time tracking, budgeting, status reporting, etc.)
- Strong sense of urgency with comfortability delivering solutions in fast\-paced, dynamic environments
- Excellent critical thinking, leadership, communication, and project management skills
- Willingness to travel for out\-of\-town client engagements (up to 30\-50% travel)
- Proven success achieving in\-year revenue expectations
- A commitment to inclusion and diversity, and openness to new ideas and perspectives
Based on pay transparency guidelines, the salary range for this role can vary based on your proximity to one of our West Monroe offices (see table below). Individual salaries are determined by evaluating a variety of factors including geography, experience, skills, education, and internal equity.
Employees (and their families) are covered by medical, dental, vision, and basic life insurance. Employees are able to enroll in our company’s 401k plan, purchase shares from our employee stock ownership program and be eligible to receive annual bonuses. Employees will also receive unlimited flexible time off and ten paid holidays throughout the calendar year. Eligibility for ten weeks of paid parental leave will also be available upon hire date.
Seattle or Washington, D.C.
$124,100 \- $146,000 USD
Los Angeles
$130,000 \- $152,900 USD
New York City or San Francisco
$135,900 \- $159,900 USD
A location not listed above
$118,200 \- $139,000 USD
### Other consultancies talk at you.
At West Monroe, we work with you.
We’re a global business and technology consulting firm passionate about creating measurable value for our clients, delivering real\-world solutions.
The combination of business and technology is not new, but how we bring them together is unique. We’re fluent in both. We know that technology alone is not the answer, but how we apply it is. We rely on data to constantly adapt and solve new challenges. Actions that work today with outcomes that generate value for years to come.
At West Monroe, we zero in on the heart of the opportunity, getting to results faster and preparing people for what’s next.
You’ll feel the difference in how we work. We show up personally. We’re right tin the room with you, co\-creating through the challenges. With West Monroe, collaboration isn’t a lofty promise, but a daily action. We work together with you to turn vision into clear action with lasting impact.
West Monroeis an Equal Employment Opportunity Employer
We believe in treating each employee and applicant for employment fairly and with dignity. We base our employment decisions on merit, experience, and potential, without regard to race, color, national origin, sex, sexual orientation, gender identity, marital status, age, religion, disability, veteran status, or any other characteristic prohibited by federal, state or local law. To learn more about diversity, equity and inclusion at West Monroe, visit www.westmonroe.com/inclusion. If you require a reasonable accommodation to participate in our recruiting process, please inquire by sending an email to recruiting@westmonroe.com.
Please review our current policy regarding use of generative artificial intelligence during the application process.
If you are based in California, we encourage you to read West Monroe’s Notice at Collection for California residents, provided pursuant to the California Consumer Privacy Act (CCPA)
Salary Context
This $124K-$159K range is above the median for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At West Monroe, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300. This role's midpoint ($142K) sits 15% below the category median. Disclosed range: $124K to $159K.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
West Monroe AI Hiring
West Monroe has 5 open AI roles right now. They're hiring across AI/ML Engineer. Positions span York, WA, US, Chicago, IL, US, Boston, NY, US. Compensation range: $146K - $304K.
Location Context
AI roles in Boston pay a median of $218,900 across 268 tracked positions. That's 19% 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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: Rag (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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