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About This Role
Ecosystem Supplier Enablement Senior Manager \| Senior Level \| Full time
Job No. R00320025 \| Multiple Locations
We Are:
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent\- and innovation\-led company with approximately 790,000 people serving clients in more than 120 countries.
A leading partner to the world’s major cloud providers, including AWS, Azure, and Google and Private Cloud leaders like IBM, Dell, HPE, RedHat. Our Cloud First group of more than 150,000 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 omni 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. Visit us at www.accenture.com.
You Are:
The Red Hat Offering Lead – Private AI, Containers \& Automation is accountable for shaping, defining, and scaling Accenture’s Red Hat–anchored offerings as a core pillar of clients’ Private Cloud, Hybrid Cloud, and AI‑enabled transformation journeys.
You own the end‑to‑end offering lifecycle—from strategy and investment prioritization through industrialization, commercialization, and market adoption—ensuring alignment with Accenture Cloud First priorities, Business Groups, Industry Groups, Service Groups, and Geographies.
This is a senior leadership role with strong practitioner credibility, operating as part of a federated community of offering and capability leads across private cloud platforms, containers, automation, and private AI. You actively shape complex client transformations while driving scale, repeatability, and differentiation across industries and regions.
The Work:
Work with practice lead leadership to set the global vision, roadmap, and investment priorities for Red\-Hat offerings that will drive the most revenue (Ex: Private AI platforms on OpenShift)
Align the offering to Accenture growth platforms and priority client demand; defining the value proposition, target clients (with market leads), priority industries and competitive differentiation – established overall desirability, feasibility, and viability.
Work with Delivery Leaders to ensure delivery readiness and capabilities are included based on business case and drive scale, repeatability, and differentiation across industries and geographies
Commercialization \& Go\-to\-Market
- Business liaison to lock down commercialization including packaging, pricing, and sales motions with proper parts of the firm.
- Partner with Sales, Industry Groups, and Geographies to generate pipeline and revenue
- Act as executive sponsor and offering SME for priority pursuits and flagship clients
Federated Leadership \& Governance
- Hire, lead and coordinate Tower Offering Leads across capability domains
- Establish governance, operating cadence, and decision rights
- Ensure integrated, end\-to\-end solutions and consistent market messaging
Alliance \& Ecosystem Leadership
- Serve as Accenture’s global counterpart to RedHat offering leadership
- Shape joint strategy, innovation agenda, and co\-investment priorities
- Influence product roadmaps and accelerate joint solution development
Asset Development \& Enablement
- Oversee industrialization of reusable assets, accelerators, and delivery models
- Ensure offerings are delivery\-ready and scalable globally with Delivery and BG Lead
- Drive enablement across sales, solutioning, and delivery communities
Strategic Vision
- Contribute to the overall practice strategy and act as a GTM leader for priority AI opportunities, shaping the evolution of offerings in line with market demand and technology trends
Travel will be required for role. Travel varies between 0\-100% depending on client/business needs.
Here’s What You Need:
- Minimum 6 years of consulting experience, preferably including strategy, platform, or transformation leadership, with the ability to navigate a highly matrixed organization, align multiple stakeholder groups, and drive measurable outcomes.
- Minimum 6 years of experience in technology or digital transformation roles, with strong understanding of private and hybrid cloud platforms, container ecosystems, and automation‑driven operating models.
- Minimum 3 years of hands‑on experience with Red Hat technologies, including OpenShift, container platforms, automation, and hybrid cloud architectures, with demonstrated practitioner experience shaping and delivering enterprise‑scale initiatives.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate’s Degree, must have minimum 6 years work experience
Professional Skills Requirement:
- Exceptional executive presence, with outstanding communication and presentation skills, and the ability to act as an influential industry evangelist.
- Ability to structure and lead story\-driven narratives for offerings across industry specializations and technology stacks.
- Proven track record of leading large\-scale business transformation initiatives driven by technology.
- Knowledge of cloud business models, and value realization across public, private, hybrid, and sovereign cloud environments.
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 06/30/2026\.
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 $132,500 to $338,300
Cleveland $122,700 to $270,600
Colorado $132,500 to $292,200
District of Columbia $141,100 to $311,200
Illinois $122,700 to $292,200
Maryland $132,500 to $292,200
Massachusetts $132,500 to $311,200
Minnesota $132,500 to $292,200
New York $122,700 to $338,300
New Jersey $141,100 to $338,300
Washington $141,100 to $311,200
Atlanta, GA
Albany, NY
Arlington, VA
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
New York City, NY
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
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Equal Employment Opportunity Statement
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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.
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Join Accenture to work at the heart of change. Visit us at www.accenture.com.
Salary Context
This $122K-$338K 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 ($230K) sits 38% above the category median. Disclosed range: $122K to $338K.
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
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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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