Interested in this AI/ML Engineer role at Logic, Inc.?
Apply Now →Skills & Technologies
About This Role
Technology Architecture Associate Director \| Senior Level \| Full time
Job No. R00313708 \| Multiple Locations
We Are
A leading partner to the world’s major cloud providers, including AWS, Azure, and Google. The formation of Accenture Cloud First, with a $3 billion investment over three years, demonstrates our commitment to deliver greater value to our clients when they need it most and offers huge growth opportunities for you! Our Cloud First group of more than 70,000 cloud professionals delivers a full stack of integrated cloud capabilities across data, edge, integrated infrastructure and applications, deep ecosystem skills, culture of change along with a deep industry expertise to shape, move, build and operate our clients’ businesses in the cloud. To accelerate our customers transformation leveraging cloud, we combine world\-class learning and talent development expertise; deep experience in cloud change management; and cloud\-ready operating models with a commitment to responsible business by design — with security, data privacy, responsible use of artificial intelligence, sustainability and ethics and compliance built into the fundamental changes Accenture helps companies achieve.
About the Accenture Google Cloud Business Group (AGBG)
We are the Accenture Google Business Group (AGBG), a team of innovators and builders changing the world with the most advanced cloud\-native solutions on the planet. As part of Accenture’s $3B investment in Cloud First, we deliver the promise of technology and human ingenuity, helping our clients navigate their most significant transformations. If you are passionate about solving exciting problems and shaping the future of technology, we would love to talk with you.
You Are
We are seeking a rare and visionary leader to architect and build our global Mainframe Modernization practice on Google Cloud. This executive role is at the nexus of legacy and innovation, focused on one of the most critical challenges facing large enterprises today: unlocking the immense value trapped within their core mainframe systems.
The Work
You will be responsible for defining the strategy, building the solutions, and leading the engagements that help our most strategic customers bridge their mission\-critical past to an AI\-driven future. Your mission is to prove that mainframe transformation is not just about cost savings, but about unleashing decades of invaluable data and business logic to power the next generation of data analytics, AI, and intelligent agents on Google Cloud.
Key Responsibilities
- Practice Development and Strategic Vision: You will be the founder and leader of Google Cloud's global Mainframe Modernization practice. This involves creating and executing the comprehensive strategy, methodology, and vision for how Google Cloud approaches the mainframe market. You will develop our core point of view, author reference architectures, and build the repeatable frameworks and best practices that will guide every customer engagement, establishing Google as the premier partner for mainframe transformation.
- Solution and Offering Incubation: You will spearhead the development of innovative, market\-leading solutions that go far beyond simple "lift and shift." This means creating offerings that intelligently connect mainframe data and applications to Google Cloud's data and AI platforms. You will lead the charge in designing solutions for real\-time data replication into BigQuery, applying Vertex AI models to decades of transactional history, creating generative AI agents that can interact with legacy business logic, and architecting secure, hybrid environments where mainframes and cloud\-native services coexist and create new value.
- Executive Advisory and Thought Leadership: You will act as Google Cloud's most senior and credible advisor on mainframe transformation, engaging directly with the C\-suite and technical leadership at the world's largest banks, insurers, retailers, and government agencies. You will guide them through the complex strategic decisions of their modernization journey. As the public face of our practice, you will establish our thought leadership by speaking at major industry events, publishing definitive white papers, and building unwavering confidence in Google's unique ability to solve this generational challenge.
- Go\-to\-Market and Sales Enablement: You will be directly responsible for empowering Google's global sales and solution architecture teams to successfully identify, pursue, and win mainframe modernization projects. This includes creating and delivering high\-impact training programs, developing sales plays and enablement materials, and personally leading the technical strategy on our most complex and strategic customer accounts. Your leadership will be instrumental in building a significant and sustainable business for Google Cloud.
- Partner Ecosystem Curation and Development: Mainframe modernization is a team sport. You will own the strategy for building and nurturing a world\-class ecosystem of partners. This involves identifying and cultivating deep relationships with key mainframe modernization software vendors (e.g., re\-hosting, refactoring, code conversion tools), data replication specialists, and global system integrators who possess the deep skills required for complex mainframe migration and transformation projects.
Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.
Here's what you need
- Bachelor's degree in Computer Science, Engineering (or a related field) or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience)
- Minimum of 15 years of experience in a senior enterprise technology role, with a significant portion focused on mainframe environments.
- Minimum of 7 years of experience and deep, hands\-on expertise with the IBM Z platform and its core subsystems (e.g., z/OS, CICS, IMS, DB2 for z/OS, JCL, COBOL, Assembler). This is essential for credibility.
- Minimum of 7 years of experience and proven track record of architecting or leading large\-scale mainframe migration, modernization, or application transformation projects for major enterprises.
Professional Skills Requirements
- Strong understanding of enterprise architecture, legacy integration patterns, and modern application development.
Bonus Points if you Have
- Direct experience with a major public cloud platform (Google Cloud Platform is strongly preferred).
- Hands\-on experience with mainframe modernization tools and techniques (e.g., Micro Focus, Blu Age, GFT, TSRI) and data replication technologies (e.g., Qlik, Fivetran, Striim).
- Experience building and leading a professional services, consulting, or technical solutions practice.
- Demonstrated experience applying modern data analytics or AI/ML techniques to solve business problems, particularly with legacy data sources.
- An extensive network of executive\-level relationships within mainframe\-heavy industries such as Banking, Financial Services, Insurance, Retail, and Public Sector.
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
We anticipate this job posting will be posted until 05/31/2026\.
Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long\-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits \| Accenture
Role Location Annual Salary Range
California $163,000 to $369,800
Cleveland $150,900 to $295,800
Colorado $163,000 to $319,500
District of Columbia $173,500 to $340,200
Illinois $150,900 to $319,500
Maryland $163,000 to $319,500
Massachusetts $163,000 to $340,200
Minnesota $163,000 to $319,500
New York $150,900 to $369,800
New Jersey $173,500 to $369,800
Washington $173,500 to $340,200
New York City, NY
Albany, NY
Arlington, VA
Atlanta, GA
Austin, TX
Beaverton, OR
Bentonville, AR
Boston, MA
Carmel, IN
Charlotte, NC
Chicago, IL
Cincinnati, OH
Cleveland, OH
Columbus, OH
Culver City, CA
Denver, CO
Des Moines, IA
Detroit, MI
Hartford, CT
Houston, TX
Irving, TX
Kirkland, WA
Miami, FL
Milwaukee, WI
Minneapolis, MN
Morristown, NJ
Mountain View, CA
Nashville, TN
Oklahoma City, OK
Overland Park, KS
Philadelphia, PA
Pittsburgh, PA
Raleigh, NC
Redmond, WA
Sacramento, CA
San Diego, CA
San Francisco, CA
Scottsdale, AZ
Seattle, WA
St. Louis, MO
St. Petersburg, FL
Walnut Creek, CA
Requesting an Accommodation
Accenture is committed to providing equal employment opportunities for persons with disabilities or religious observances, including reasonable accommodation when needed. If you are hired by Accenture and require accommodation to perform the essential functions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.
If you would like to be considered for employment opportunities with Accenture and have accommodation needs such as for a disability or religious observance, please call us toll free at 1 (877\) 889\-9009 or send us an email or speak with your recruiter.
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Accenture is an EEO and Affirmative Action Employer of Veterans/Individuals with Disabilities.
Accenture is committed to providing veteran employment opportunities to our service men and women.
Other Employment Statements
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.
Candidates who are currently employed by a client of Accenture or an affiliated Accenture business may not be eligible for consideration.
Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process. Further, at Accenture a criminal conviction history is not an absolute bar to employment.
The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.
California requires additional notifications for applicants and employees. If you are a California resident, live in or plan to work from Los Angeles County upon being hired for this position, please for additional important information.
Please read Accenture’s Recruiting and Hiring Statement for more information on how we process your data during the Recruiting and Hiring process.
We work with one shared purpose: to deliver on the promise of technology and human ingenuity. Every day, more than 775,000 of us help our stakeholders continuously reinvent. Together, we drive positive change and deliver value to our clients, partners, shareholders, communities, and each other.
We believe that delivering value requires innovation, and innovation thrives in an inclusive and diverse environment. We actively foster a workplace free from bias, where everyone feels a sense of belonging and is respected and empowered to do their best work.
At Accenture, we see well\-being holistically, supporting our people’s physical, mental, and financial health. We also provide opportunities to keep skills relevant through certifications, learning, and diverse work experiences. We’re proud to be consistently recognized as one of the World’s Best Workplaces™.
Join Accenture to work at the heart of change. Visit us at www.accenture.com.
Salary Context
This $150K-$369K range is above the 75th percentile 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 Logic, Inc., 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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($260K) sits 56% above the category median. Disclosed range: $150K to $369K.
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.
Logic, Inc. AI Hiring
Logic, Inc. has 47 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer, AI Consultant. Positions span New York, NY, US, Atlanta, GA, US, Chicago, IL, US. Compensation range: $93K - $434K.
Location Context
AI roles in New York pay a median of $200,000 across 1,670 tracked positions. That's 9% 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.